Table Of Contents

• Digital Transformation Companies Comparison Table
• Top Digital Transformation Companies
  • Accenture: Best For Reporting Insights
  • Deloitte: Best For Scalability
  • Boston Consulting Group: Best For People-Focused Consultation
  • Cognizant: Best For Company Culture
  • Capgemini: Best For Telecommunications
  • Microsoft Corporation: Best For Industry Cloud
  • McKinsey & Company: Best For Subject Matter Expertise
• Benefits of Working With a Digital Transformation Company
• How To Choose What Digital Transformation Companies Best For You
• Bottom Line: Digital Transformation Companies

Digital Transformation Companies Comparison Table

Top Digital Transformation Companies

The top digital transformation companies all offer feature-rich services at varying prices. For example, a consulting engagement with these companies can help your business transform billing and payment processing, provide better analytics and reporting to gain deeper insights into customer behavior, and improve infrastructure across your organization. In short, digital transformation service providers can help your business keep up with the competitive nature of technology and industry needs.

Your business’s specific needs and budget will determine which company is the right fit, but comparing pricing can be a challenge. It is not uncommon for digital transformation providers not to disclose pricing publicly because it is dependent upon the particular tools and services involved, the complexity and duration of the engagement, and other factors that make it difficult to offer a one-size-fits-all pricing strategy.

When selecting a provider, consider the use cases outlined below to find those that best meet your specific needs and then contact those providers to get cost estimates for the right solutions to address them.

Accenture: Best For Reporting Insights

Accenture’s digital transformation services are part of its Technology Strategy and Advisory Practice, and include assistance with cloud acceleration, data-driven company tools, operating models and innovation, network connection services, and modern architecture using the Accenture Momentum digital transformation tool.

Features

• Real-time Reporting: Accenture’s digital transformation tools track the status of initiatives such as assessing, reviewing, and resolving risks.
• Value Drivers: The company’s digital transformation tools build and visualize value trees to create complete business cases using many details to help with individual initiatives.
• Forward-looking Insights: Accenture Momentum provides reporting dashboards for dynamic views and drill-downs.

Pros

• Holistic evaluations
• Processing oriented systems
• Strong service delivery system and personnel

Cons

• Limited data flexibility
• Limited dynamic frameworks
• Slow delivery timelines

Pricing

Accenture does not list pricing on its website. However, it recently introduced Manage myPrice, its new approach to pricing. For more detailed information, contact sales.

Deloitte: Best For Scalability

Deloitte’s digital transformation capabilities are incorporated within its Strategy and Analytics business as well as its Monitor Deloitte arm. Deloitte aims to help enterprises with the capacity for change to help fuel growth, practice continuous transformation, and harness insights.

Features

• Intelligent Mining: Deloitte assists companies in implementing sustainable transformation by offering the required multidisciplinary skills and industry experience needed.
• Business Scalability: It helps companies realize and refine their digital transformation vision by providing flexibility and offering integrated delivery teams for an agile operation.
• Concept Refinement: Deloitte offers iterative concept refinement and faster income statements through its Deepen, Design, and Prove steps.

Pros

• Excels at integrating technology
• Experts in DevOps and automation
• Helps with multi-cloud setup

Cons

• Limited technology capabilities
• High prices
• Heavy research needed

Pricing

Deloitte does not list prices on its site. Contact the sales team or see the pricing strategy page to learn more, or send a Request for Proposal.

Boston Consulting Group: Best For People-Focused Consultation

Boston Consulting Group (BCG) describes its digital transformation capabilities as focused on people and technology. Its six steps of success include crafting a clear strategy, commitment to leadership from top to middle, putting the best employees for the job in the right place, having an agile government mindset, monitoring and controlling progress, and creating a business-led data platform.

Features

• Digital Skill-Building: BCG’s digital transformation is about evolving employee and business capabilities in such areas as data science, location strategies, and finding the balance between insourcing and outsourcing.
• Operating Model Transformation: BCG’s goal is to work to align governance, processes, and organizational structure with a platform-driven operating model.
• Outcomes Implementation: Digital transformation practices include identifying, prioritizing, and implementing high-impact use cases for your company.

Pros

• Highly regarded consultants
• Wide range of capabilities
• Fees based on agreed-upon Key Performance Indicators (KPIs)

Cons

• Not for small companies
• A slow-paced approach
• No specific tools used

Pricing

The Boston Consulting Group offers a pricing page but does not offer specific pricing. Contact sales for more information.

Cognizant: Best For Company Culture

Cognizant offers digital transformation services through its Digital Strategy umbrella. Its goal is to keep up with customer demands across all sides of a business to ensure relevancy in its infrastructure. Cognizant’s digital transformation services offer insight into transformation, managed innovation, workforce transformation, change adoption, and transformation enablement. The offerings aim to create a positive company strategy that adds agile processes and a digital approach in different departments within the company.

Features

• Transformation Insights: Customers improve their insights through reinvention, offering an agile approach and using execution expertise.
• Managed Innovation: Insight-driven processes develop client solutions with new forms of value to establish, nurture, and grow innovation capabilities.
• Change Adoption: Cognizant’s change adoption offers digital tools to enable growth and agility with a structured approach to help clients with their adoption rate and pace with business change all around them.

Pros

• Strong cloud technology
• Diverse technical services
• Flexible payment model

Cons

• Limited location access
• Weak strategy capabilities
• Limited customer service help

Pricing

Cognizant does not list pricing. However, it does provide a pricing and fees page that offers direct contact and lists available products and services. Contact sales to discuss a payment model.

Capgemini: Best For Telecommunications

Capgemini’s digital transformation services are focused on the telecommunications industry to help accelerate the transformation from communication service providers to digital service providers. For B2C operators, it enables new value digital proposals; for B2B, it offers the ability to rewire and reboot customer experience and operational excellence. For vertical industries, it will help increase revenue and efficiency with the better-connected world.

Features

• Customer-First B2C: Capgemini promotes designing digital and market-facing services to design business models and operations to support connected experiences to provide value.
• B2B Omni-Channel Customer Experience: Capgemini aims to improve customer experience and help transform companies into digital service providers.
• 5G Monetization: The company’s support for vertical industries helps them make the most of revenue and efficiency opportunities in the current digital world.

Pros

• Deep digital expertise
• Flexible approach to digital transformation
• Helps with customer’s self-funded projects

Cons

• Limited global expertise
• Limited strategy capabilities
• Expensive platform

Pricing

Capgemini’s site explains its PriceLab pricing tool but does not provide specific pricing. Contact the company to learn more.

Microsoft Corporation: Best For Industry Cloud

Microsoft is a top tech company whose digital transformation services focus on five industries: financial services, government, health care, manufacturing, and retail. It has led with digital transformation by modernizing platforms with Microsoft 365 and Azure Edge, helping organizations find solutions to fix common issues, giving data and analytics assistance, and helping them further engage with customers.

Features

• Industry Cloud: Azure Cloud helps companies gain agility while accelerating innovation in a specific industry.
• Customer Relationship Management: Microsoft’s digital transformation services help companies reach more customers by outperforming competitors with new innovative digital agility.
• Artificial intelligence (AI) For Digital Transformation: AI benefits digital transformation by increasing intelligent marketing, by adding innovation to the current infrastructure, and with analysis.

Pros

• Wide range of services
• Strong documentation
• Reliable known company

Cons

• Limited navigation help
• Complicated networking
• Limited reporting ability

Pricing

Microsoft is the most transparent provider of the seven when it comes to pricing, and offers estimated pricing based on which tools a customer uses. Use Microsoft’s pricing calculator, which also lists digital transformation products. Contact sales for more information.

McKinsey & Company: Best For Subject Matter Expertise

McKinsey & Company’s digital transformation service, McKinsey Digital, helps businesses add capabilities such as AI and other new technologies to automate operations, encourage digital growth, create unique digital experiences, and improve customers’ digital talent and culture.

Features

• Speed Of Impact: McKinsey Digital aims for a quick impact to generate higher cash flows and is dependent on temporary subject matter experts to fill roles within companies.
• Long-term Sustainability: McKinsey Digital addresses and emphasizes capability building, organizational setup, and improvement to give a continuous impact.
• Emphasis On Innovation: McKinsey Digital offers companies the ability to invest heavily in their IT departments to build completely new infrastructure and have more subject matter experts.

Pros

• Highly regarded company
• Many projects completed
• Pilot testing before expanding to other parts of the company

Cons

• Known to be expensive
• Limited technical capabilities
• Hard-driving attitude

Pricing

McKinsey & Company does not list pricing on its website, but provides a pricing article that explains how customers are charged. Contact sales to get a quote.

For more: 5 Digital Transformation Examples

Benefits of Working With a Digital Transformation Company

Digital transformation supports the business in multiple ways, and a good digital transformation consultant will work with customers to create a framework that does the following:

• Boosts Performance: Digital transformation helps keep up with new technology and improves performance, such as adding automation to complete menial tasks and free up resources for strategic work.
• Improves Company Communication: Digital transformation provides staff with new communication skills and tools, and enables business improvements.
• Enhances Innovation: Digital transformation can provide better access and insights to help innovate new products and services and new ways of doing things.
• Informs Decision-Making: Because digital transformation uses analytic tools, it provides insight into the correct decision on what’s best for a company and its data.

How To Choose a Digital Transformation Company 

There are several criteria to weigh when looking to choose the right digital transformation services provider.

Outline a Strategy

When a business looks into working with a digital transformation company, it should know exactly what it wants from the process. Finding a provider to help refine and execute a digital strategy can be more effective than rushing into an engagement without planning ahead.

Research Providers

Before picking a digital transformation provider, research the company and its customer stories. If it is meeting the needs of similar companies and the case studies sound familiar, it’s more likely to be a good fit for your own needs too.

Inventory Tool Stack

Digital transformation requires measuring the effectiveness of your current infrastructure and tool stack. For example, if a company uses a cloud-based infrastructure, on-site equipment likely will not help during the transformation process—technologies must support each capability. Before taking on a digital transformation project, make an inventory of existing tools to provide a more clear picture of what the transformation will encompass.

Consider Budget

While it can be difficult to compare prices from providers, a company considering a digital transformation project should know what it can spend and what it is willing to invest. Narrow down providers by their ability to meet specific needs, and then work with their sales teams to price out an engagement. Providers can also help organizations calculate the potential ROI of such a project and help with cost/benefit analysis.

Bottom Line: Digital Transformation Companies

When considering a digital transformation provider, it is vital for companies to weigh features and costs against their primary goals, including refining and executing their strategies and frameworks. While each digital transformation consulting firm offers a variety of services, matching them to specific use cases can help companies evaluate them against their specific needs.

For more information on digital transformation: Data Transformation Trends

For businesses considering a data warehouse solution, a number of competing providers offer a range of features and prices. This article will compare the top seven solutions and explain the features that differentiate them, making it easier to match them to specific needs.

Table Of Contents

• Top Data Warehouse Providers And Solutions
• Data Warehouse Providers And Solutions Comparison Table
• Amazon Redshift: Best For Deployment Optimization
• Google BigQuery: Best For Serverless Data Warehousing
• IBM Db2 Warehouse: Best For Analytic Workloads
• Azure Synapse Analytics: Best For Code-Free Offering
• Oracle Autonomous Data Warehouse: Best For Integration
• SAP Datasphere: Best For Data Warehouse Templates
• Snowflake: Best For Cloud Data Warehouses
• Key Features Of Data Warehouse Providers And Solutions
• How To Choose What Data Warehouse Provider Best For You
• Frequently Asked Questions (FAQ)
• Bottom Line: Data Warehouse Providers And Solutions

Top Data Warehouse Providers and Solutions

The top seven providers all offer feature-rich data warehousing plans at varying prices. A business’s specific needs will determine which is right for them. When selecting a provider, consider the use cases and costs for each as outlined below.

Data Warehouse Providers And Solutions Comparison Table

Amazon Redshift: Best For Deployment Options

With Amazon’s entry into the cloud data warehouse market, Redshift is an ideal solution for those organizations that have already invested in AWS tooling and deployment. Redshift deploys with Software as a Service (SaaS), cloud, and web-based solutions.

Pricing

Amazon Redshift has a pricing page where users can sign up for a trial period, request a quote, or calculate costs based on needs. Pricing starts at $0.25 an hour and can be configured using various models based on usage.

Features

• Spectrum Feature: This feature allows organizations to directly connect with data stores in the AWS S3 cloud data storage service, reducing startup time and cost.
• Strong Performance: The performance benefits companies from AWS infrastructure and large parallel processing data warehouse architecture for distributed queries and data analysis.
• Integration With AWS Glue: AWS Glue makes it easy to write or autogenerate Extract, Transform, and Load (ETL) scripts in addition to testing and running them.

See all Redshift features at https://aws.amazon.com/redshift/features.

Pros

• Parallel processing capabilities
• Contains network isolation security
• Good documentation

Cons

• Expensive
• Poorly designed user interface
• Unable to restrict duplicate records

For more on AWS: AWS Data Portfolio Review

Google BigQuery: Best For Serverless Technology

Google BigQuery is a reasonable choice for users looking to use standard SQL queries to analyze large data sets in the cloud. It is a serverless enterprise data warehouse that uses cloud, scale, Machine Learning (ML)/Artificial Intelligence (AI), and Business Intelligence (BI).

Pricing

Google BigQuery’s pricing page contains specific information about pay-as-you-go plans and longer-term (one to three year) commitments. The provider offers multiple versions of the platform, including Enterprise Edition and Enterprise Plus Edition. The Standard Edition is a pay-as-you-go plan starting at $0.04 per slot hour and the Enterprise Edition has different plans to help a company find its cloud data warehouse.

Features

• Serverless Technology: Using serverless technology, Google handles the functions of a fully managed cloud service, data warehouse setup, and resource provisioning.
• Logical Data Warehousing Capabilities: BigQuery lets users connect with other data sources, including databases and spreadsheets to analyze data.
• Integration With BigQuery ML: With BigQuery ML machine learning, workloads can be trained on data in a data warehouse.

See all BigQuery features at https://cloud.google.com/bigquery.

Pros

• Works with Google Cloud
• Full SQL query support
• Efficient management of data

Cons

• No user support
• Difficult for beginners in data warehouses
• Difficult user interface

For more information on Google: Google Data Portfolio Review

IBM Db2 Warehouse: Best For Analytic Workloads

IBM Db2 Warehouse is a strong option for organizations handling analytics workloads that can benefit from the platform’s integrated in-memory database engine and Apache Spark analytics engine.

Pricing

IBM offers a free trial for IBM Db2 Warehouse and provides a pricing page where users can ask for a quote and estimate the cost. For the flex one plan, the pricing is $1.23 per instance-hour, $0.99 per VPC-hour, and $850 per a service endpoint dedicated connectivity.

For more information, go to IBM’s pricing page.

Features

• Helpful Integration: IBM Db2 Warehouse integrates an in-memory, columnar database engine, which can be a big benefit for organizations looking for a data warehouse that includes a high-performance database.
• Netezza Technology: Db2 Warehouse benefits from IBM’s Netezza technology with advanced data lookup capabilities.
• Cloud Deployment And On-Premises: Deployment can be done in either IBM cloud or in AWS, and there is also an on-premises version of Db2 Warehouse, which can be useful for organizations that have hybrid cloud deployment needs.

See all Db2 Warehouse features at https://www.ibm.com/products/db2/warehouse.

Pros

• Includes in-memory columnar database
• Cloud deployment options
• Configuration flexibility

Cons

• Expensive
• Limited references online
• Limited buffer pool commands

For more on IBM: IBM: Hybrid Cloud Portfolio Review

Azure Synapse Analytics: Best For Code-Free Offerings

Azure Synapse Analytics, previously known as Azure SQL Data Warehouse, is well suited for organizations of any size looking for an easy on-ramp into cloud-based data warehouse technology, thanks to its integration with Microsoft SQL Server.

Pricing

Azure Synapse Analytics’s pricing page allows customers to request a quote or explore pricing options. For tier one, Azure offers 5,000 units for $4,700; tier two offers 10,000 units for $9,200. For other tier options, refer to the pricing page.

Features

• Dynamic Data Masking (DDM): Azure Synapse Analytics provides a granular level of security control, enabling sensitive data to be hidden on the fly as queries are made.
• Azure Integration: Existing Microsoft users will likely find the most benefit from Azure SQL Data Warehouse, with multiple integrations across the Microsoft Azure public cloud and more importantly, SQL Server for a database.
• Parallel Processing: In contrast to simply running SQL Server on-premises, Microsoft has built on a massively parallel processing architecture that can enable users to run over a hundred concurrent queries.

See more Azure Synapse Analytics features at https://learn.microsoft.com/en-us/azure/synapse-analytics/whats-new.

Pros

• Easy integration
• Some code-free offerings
• Strong data distribution

Cons

• Difficult logging metrics
• Limited diagramming tools
• Limited documentation

For more on Microsoft Azure: Microsoft Azure: Cloud Portfolio Review

Oracle Autonomous Data Warehouse: Best For Integration

For existing users of the Oracle database, the Oracle Autonomous Data Warehouse might be the easiest choice, offering a connected onramp into the cloud including the benefits of data marts, data warehouses, data lakes, and data lakehouses.

Pricing

Oracle’s Autonomous Data Warehouse’s main page offers pricing information as well as a cost estimator for users. The bottom price for Oracle Autonomous Data Warehouse shared and dedicated infrastructures is $0.25 per unit.

Features

• Works With Cloud And Hardware: A key differentiator for Oracle is that it runs the Autonomous Data Warehouse in an optimized cloud service with Oracle’s Exadata hardware systems, which has been purpose-built for the Oracle database.
• Easy Collaboration: The service integrates a web-based notebook and reporting services to share data analysis and enable easy collaboration.
• Strong Integration: While Oracle’s namesake database is supported, users can also migrate data from other databases and clouds, including Amazon Redshift, as well as on-premises object data stores.

See more features at https://www.oracle.com/autonomous-database/autonomous-data-warehouse/.

Pros

• Migration support for other database services
• Purpose-built hardware
• Fast query performance

Cons

• No on-premises solutions
• Limited data connection
• Complicated setup

For more on Oracle: Oracle Data Portfolio Review

SAP Datasphere: Best For Templates

Thanks to the pre-built templates it offers, SAP’s Datasphere might be a good fit for organizations looking for more of a turnkey approach to getting the full benefit of a data warehouse. SAP Datasphere allows data professionals to deliver scalable access to business data.

Pricing

SAP Datasphere’s pricing page lists a free tier and range of flexible pricing options based on needs. The price for capacity datasphere units is $1.06 per unit.

Features

• SAP’s HANA (High-performance Analytic Appliance): The cloud services and database are at the core of Data Warehouse Cloud, supplemented by best practices for data governance and integrated with a SQL query engine.
• Pre-Built Business Templates: Templates can help solve common data warehouse and analytics use cases for specific industries and lines of business.
• Integration with SAP Applications: SAP Datasphere integration means easier access to on-premises as well as cloud data sets.

See more features including a product demo at https://www.sap.com/products/technology-platform/datasphere.html.

Pros

• Inventory controls
• Extract data from multiple sources
• Strategic solutions

Cons

• Difficult for beginners
• Difficult integration
• Limited visual analytics

For more on SAP: SAP Data Portfolio Review

Snowflake: Best For Data Warehouse In The Cloud

Snowflake is a great option for organizations in any industry that want a choice of different public cloud providers for data warehouse capabilities. Snowflake aims to bring development to data, help companies govern data for users, and work globally and cross-cloud.

Pricing

Snowflake’s pricing page links to a quote page and offers a 30-day free trial with $400 of free usage.

Features

• Database Engine: Snowflake’s columnar database engine capability can handle both structured and semi-structured data, such as JSON and XML.
• Cloud Provider Of Choice: Snowflake architecture allows for compute and storage to scale separately, with data storage provided on the user’s cloud provider of choice.
• Virtual Data Warehouse: The system creates what Snowflake refers to as a virtual data warehouse, where different workloads share the same data but can run independently.

See more features at https://www.snowflake.com/en/.

Pros

• SQL-based queries for analytics
• Support for JSON and XML
• Integration with AWS, Azure, and GCP

Cons

• Limited data visualization
• Unable to create dynamic SQL
• Difficult documentation

For more information on Snowflake: Snowflake and the Enterprise Data Platform

Key Features of Data Warehouse Providers and Solutions

Cloud data warehouses typically include a database or pointers to a collection of databases where the production data is collected. Many modern cloud data warehouses also include some form of integrated query engine that enables users to search and analyze the data and assist with data mining.

Other key features to look for in a cloud data warehouse setup:

• Integration or API Libraries
• Data Quality and Compliance Tools
• ETL Tools
• Data Access Tools/Database Searchability
• SQL and NoSQL Data Capabilities

For more features and benefits: Top 10 Benefits of Data Warehousing: Is It Right for You?

How To Choose Which Data Warehouse Provider is Best for You

When looking to choose a cloud data warehouse service, there are several criteria to consider.

Existing Cloud Deployments. Each of the major public cloud providers has its data warehouse that provides integration with existing resources, which could make deployment and usage easier for cloud data warehouse users.

Ability to Migrate Data. Consider the different types of data the organization has and where it is stored. The ability to migrate data effectively into a new data warehouse is critically important.

Storage Options. While data warehouse solutions can be used to store data, having the ability to access commodity cloud storage services can provide lower-cost options.

Bottom Line: Data Warehousing Providers and Solutions

When considering providers and solutions of data warehousing, it’s important to weigh features and cost against your company’s primary goals, including deployment and analytic needs and cloud services.

While each provider and solution offers a variety of features, identifying a company’s own use case can help better evaluate them against a company’s needs.

For more information: 15 Best Data Warehouse Software & Tools

For example, a business might aggregate a pool of 1,000 customers by their locations, by their purchases, or by their demographics—gender and age—to better understand customer behavior and buying decisions.

Aggregated data can be analyzed and reported on to provide insights about particular resources or resource groups, and data aggregation plays a role in both data analytics and Business Intelligence (BI).

Table of Contents

• The Process Of Data Aggregation
• Benefits Of Data Aggregation
• Who Uses Data Aggregation?
• Manual Vs. Automated Data Aggregation
• Top Data Aggregation Tools
• Bottom Line: Data Aggregation

The Process Of Data Aggregation

Data aggregation is done using data aggregation software tools that typically include features for collecting, processing, and presenting aggregate data.  Some perform highly specialized single tasks to meet specific use cases.

Aggregation is done on varying scales, and data can be aggregated over different time frames—for example, a business might gather data from a few hours of website traffic to monitor customer behavior, or from five years to show long-term trends.

Data aggregation is a three-step process:

1. Collection: Data aggregation tools extract data from one or multiple sources, storing it in large databases or data warehouses as atomic data. Atomic data is the smallest unit into which data can be broken down.
2. Processing: Extracted data is processed by the database, aggregation software, or middleware. In this step, the data is “cleaned”—errors are corrected, formatting rules are applied, and garbage data is discarded.
3. Presentation: The aggregate is then presented in a readable form, such as charts or statistics, to be presented to non-technical users.

Benefits Of Data Aggregation

Data aggregation can benefit businesses in multiple ways. Here are a few of them:

Provides Insights Through Extracted Data

Data collection and data analysis are separate processes, and data does not always need analysis. Sometimes aggregate data can reveal information that can lead a business to make a change.

Enables Statistical Analysis

Aggregation facilitates the statistical analysis of large amounts of data which can lead to the discovery of patterns and trends.

Improves Data Quality

Data aggregators automatically collect, clean, and summarize data that can be shared for collaboration. Data aggregators can reduce labor, communication overhead, save time, energy, and money.

For more tools for data quality: Best Data Quality Tools & Software

Leads to Better Decision-Making

Data aggregation collects and summarizes information across the entire company, allowing a business to see the big picture.

Who Uses Data Aggregation?

Data is a vital source of information for all industries and at all levels. Businesses rely on data analysis for everything from price-setting and product development to planning, hiring, and marketing. Here are some of the ways data aggregation can be used across different industries.

• Marketing teams can aggregate data from campaigns and the different channels they use to reach customers. They might aggregate data from a specific campaign to see how it performed over time, and then aggregate the results of that campaign with others to see how it compares. Or they might aggregate data from each specific campaign and compare them to each other to see how they are being received across channels, populations, and cohorts.
• Websites, particularly content-driven sites, can aggregate visitors by location, time of visit, time spent, and which content was popular and which was not to understand the behavior of site visitors over time and improve engagement and retention.
• E-commerce sites can aggregate data from a time of day to understand peak and low visits, visitor demographics, the number of transactions, and whether customers made purchases based on recommendations. They can also aggregate data about competitors—like product offerings, promotions, and prices—to learn what they’re up against.
• Because the news can drive stock market activity, financial and investment firms are becoming more dependent on news-related data. Aggregating headlines and article copy can provide data for predictive analytics.
• Despite the tight burdens of such regulatory compliance as HIPAA, even the healthcare industry can benefit from aggregation—especially case analysis. By aggregating the data of numerous similar cases, medical experts can come up with more effective treatment methods to accelerate overall healthcare treatment.

Manual Vs. Automated Data Aggregation

Manual aggregation is, as the name implies, the process of gathering and extracting data and aggregating it manually—in a spreadsheet, for example. This can be a time-consuming process with a high risk of errors, which means it is better-suited to small amounts of data. It also has the potential to overlook some data.

Automated data aggregation is the process of using tools to extract and aggregate data from sources automatically. This can be done on a recurring basis at regular intervals.

Given the enormous amounts of data that businesses are capable of gathering, manual aggregation is increasingly less feasible than automation through data aggregators.

Top Data Aggregation Tools

Here are some of the most widely used data aggregation tools:

1. Microsoft Excel

Excel is a hidden gem of analytics with remarkable power and capability to load from data stores, clean and process data, and generate reports. It is often the entry-level tool for people new to analytics, and there are plenty of web resources on the subject.

2. Cloudera Distribution for Hadoop (CDH)

CDH is aimed at enterprise-class businesses with an emphasis on big data. The open source tool has a free platform distribution that encompasses Apache Hadoop, Apache Spark, Apache Impala, and more technologies, all for collecting and processing huge amounts of data. There is a commercial version as well.

3. MongoDB

MongoDB is a NoSQL, document-oriented database that comes in three “flavors”: free-to-use, small-to-medium business, and enterprise. The open source tool supports multiple operating systems, and its main features include aggregation, ad hoc queries, indexing, replication, and sharding—a means of splitting large datasets into manageable chunks.

4. Sisense

Sisense is a popular software package for preparing, analyzing, visualizing, and organizing data for a business, and is designed to address inquiries directly through a single channel as well as gather and present data as relevant insights through interactive dashboards.

5. Zoho Analytics

Zoho Analytics is a popular BI, data analytics, and online reporting tool for creating data visualizations and generating actionable business insights. Zoho Analytics is designed to be used by anyone regardless of their technical skills.

6. DbVisualizer

DbVisualizer is a feature-rich database management tool for consolidating and visualizing information from across multiple database applications. Developers and analysts can manage multiple databases and configure tables with the software’s drag-and-drop interface, and it also comes with an advanced SQL editor to write SQL queries.

7. Google Looker

Looker, which was acquired by Google, is a cloud-based data-discovery platform that provides companies with real-time access to relevant data to make better business decisions. Primarily a BI platform, it allows users to explore and transform data, but also to create reports and make them accessible to everyone.

8. Stata

Stata is a data analysis and statistical software solution designed and developed specifically for researchers from different disciplines, ranging from epidemiology to political science. It offers a point-and-click graphical user interface, comprehensive statistical tools, command-line features, complete data management capabilities, and publication-quality graphs.

9. Alteryx

Alteryx is focused on what it calls analytic process automation (APA), which unifies analytics, data science and machine learning (ML), and business process automation into one end-to-end platform to accelerate digital transformation, and is designed to be used by non-technical staff.

10. IBM Cloud Pak for Data

IBM Cloud Pak for Data is a fully integrated data and AI platform that modernizes how businesses collect, organize, and analyze data, forming the foundation to apply AI across their organizations. Built on Red Hat OpenShift, and available on any cloud, it is designed to help companies accelerate and manage the end-to-end AI lifecycle.

11. GoSpotCheck

GoSpotCheck is one of the top data collection tools for businesses that depend on gathering field data. It collects data in real-time and analyzes it instantly to help users complete tasks right then and there. It is mobile-based with built-in content collection and distribution that makes sharing information with the rest of the team easy.

12. Repsly Mobile CRM

Repsly Mobile CRM is a premier all-in-one field management CRM tool. It is a cloud-based field service software for mobile sales teams and fits SMB needs and covers a range of different industries. It provides a detailed customer history, data collection with fully customizable mobile forms, and real-time visibility into how a company’s brand and their competitors are presented at retail.

For data analysis software: Top Data Analytics Tools

Bottom Line: Data Aggregation

Data aggregation is a means of gathering raw data from multiple sources and simplifying it for statistical analysis and reporting. Aggregated data can be analyzed and reported on to provide insights about particular resources or resource groups, making it a vital source of information for all industries and at all levels.

For more information on big data: Big Data Trends and The Future of Big Data

Samuel Pasquier Q&A

How Did You First Start Working In The IoT Market?

In November 2015, after having spent 10 plus years working in Cisco’s Enterprise switching product lines. I wanted to expand my scope and take on a new challenge with a new market. Cisco offered me this opportunity and It’s been an amazing 8 plus years.

What Is Your Favorite Thing About Working At Cisco?

It’s hard to pick one thing, but I can break it down to three main things. I love the IoT space and the technologies we build. Every day I’m working with customers and our internal teams to connect people and the physical world with great technology to create a better future for everyone. That brings me to number two – and that’s the people. I love our teams who bring their amazing experience, spirit, and dedication to helping our customers achieve success. We do that with a lot of hard work and also fun mixed in. And I can’t leave out Cisco. It’s a great company to work for with great values and amazing leadership. We continually win Best Place to Work and I do feel that way about the company as well.

What Sets Cisco’s IoT Approach Or Solutions Apart From The Competition?

Cisco understood very early on that to get the promise of IoT, you need to get people working together. For us, that’s usually the IT teams that have built out decades of networking infrastructure collaborating with the operational technology (OT) teams. These OT teams are running the manufacturing sites, power grids, highway departments, mines, ports, and so many other industries where technology is empowering the operations. That’s where we really stand apart from the competition—combining decades of Cisco networking experience with our expertise in these operational settings.

The IoT Market

What Is One Key New IoT Technology That Particularly Interests You?

IoT isn’t a single technology. It’s more an umbrella term about how technologies can be leveraged to help drive outcomes for organizations. It’s about connecting IT to the physical world to improve business outcomes, make operations more efficient, and make the world safer and more secure.

The interesting part for me is exactly that—that IoT is a set of technologies that need to work together and that we get to spend our days figuring out how to constantly improve on that.

Asking me to pick one is like being asked to pick your favorite child. If I have to pick, I would say LoRaWAN (Editor’s note: low-power, wide area networking protocol built on top of the LoRa radio modulation) as it’s a disruptive technology that enables new use cases that were not previously affordable.

What Is One New IoT Technique That Teams Should Implement?

For me, it’s not so much a question of technique but a question of culture. Our customers have teams with very different backgrounds and responsibilities. You need to find ways for them to collaborate and work cross functionally to digitize their processes.

What Is One New IoT Strategy That Companies Should Implement?

Over the last 8 years working within the IoT space, I have observed that the most successful companies leveraging technology to improve their business have really started by changing the way they look at the problem. They create internal organizations with a mix of skills/experience/expertise. Then they are able to have these interdisciplinary teams work together to solve their key challenges without the boundaries of internal team organization. So to be successful, organizations first need to have the right people organization to lead the change.

What Is The Biggest IoT Mistake You See Enterprises Making?

I have seen a lot of enterprises creating some digitization offices, or innovation teams to help transform the business. Unless it’s really built-in to the business/organizational entities, it generally has a very hard time to go beyond the proof-of-concept phase. We all love great ideas but enterprises need to have teams involved that can scale and deploy the solutions as well.

What Are Some Current Trends In The IoT Market That Are Promising?

As we look to the future, we see clear trends in industrial operations—more use of cloud-based applications, virtualization of control functions, and more artificial intelligence/machine learning (AI/ML)–powered analytics. Software-defined approaches will use software to manage and optimize the entire manufacturing process, including product design, scheduling, supply chain management, quality control, and maintenance. “Digital twin” technology will simulate a product from its design, production, and performance when deployed and optimizes the product and production system before investment in physical prototypes and building of assembly lines.

These uses are possible only through high-performance networking, built-in security, and machine-to-cloud connectivity. I am proud to say that Cisco Industrial Ethernet switches and the rest of our IoT portfolio is gearing up to lead this charge.

What Are The Biggest Factors That Are Driving Change In IoT?

I can’t overstate the impact of security on the IoT market. Organizations need to accelerate their security posture in the networks and operational spaces. Cybersecurity remains one of the top drivers in the IoT space. As they look to digitize their operational environments, they need to do this with security built in.

The collaboration between IT and OT is also accelerating. As organizations digitize and transform their operational settings, these teams are coming together to leverage existing technology investments and their collective expertise.

Another leading factor is supporting organizations on their sustainability journey. New types of initiatives like electric vehicle (EV) charging networks, energy storage, and carbon capture and storage are becoming more common.

How Has IoT Changed During Your Time In The Market?

I’ve seen first-hand the shift from awareness of IoT technologies to a progression of proof of concepts and now the acceleration of deployments across industries.

It was 20 years ago, March 2003, that we launched our first industrial ethernet switch and entered the industrial networking market. At that time, we arrived to support industrial organizations in adopting IP connectivity throughout their operations, along manufacturing lines, inside electric substations, deep inside mines and beyond. The past two decades have brought an explosion in the number and variety of applications that IT and operational technology teams are supporting—often in some of the wettest, dustiest, non-climate-controlled places on Earth.

Personnel in IoT

If You Could Give One Piece Of Advice To An IoT Professional In The Beginning Of Their Career, What Would It Be?

I’d say that you should accept that you need diverse expertise to be successful in an IoT Project. It’s not about IT vs OT. It’s IT + OT + security teams working together.

With The Shortage Of Tech Talent, How Is Your Team Finding And Retaining Professionals To Work In IoT?

Cisco has extensive programs to ensure that we attract and retain great talent across the organization, from our university hiring programs, veteran programs, return to work, and more. For us in IoT, my teams tell me that the reason they love working is seeing first hand the great outcomes we are delivering for our customers. With IoT, you get the benefit of seeing first-hand how IoT is improving organizations—more efficient manufacturing plants, weaving renewables into the grid, making the roads safer, and more.

For The Greatest Business Impact, What Should IoT Professionals Be Focusing On Most In Their Roles?

To bring the greatest business impact, IoT professionals should think about scale and operational aspects from the beginning of any project. Proof of concepts are easy; production deployment at scale that will need years of support are much harder.

Work-Life

What Is One Of Your Top Professional Accomplishments?

I take great pride in building great teams and getting everyone to work together. We spend so much of our time at work. It’s really important to have teams that work with great people accomplishing great things.

What Is Your Favorite Part Of Working In The IoT Market?

I love how we can leverage technology to solve a real customer problem. In a world that is more virtual than ever, it’s nice to see the very direct impact of technology with the physical world. Seeing a tangible outcome makes the work likewise tangible and rewarding.

What Is One Of Your Favorite Parts Of The Work Week? How Does It Encourage Or Inspire You?

I meet three or more customers a week which affords me the opportunity to learn directly from them, hear their business/challenges, and understand their view on technology. It’s a great way to step back from the kitchen to understand what they really need.

Do You Have A Favorite Way To Recharge During The Workday?

I start my day very early with a one-hour workout at 5:30am. It sounds crazy and I was the first person to be confused how people do this. But it’s actually very energizing and helps me tremendously to keep my mind in check during the long work hours.

What Are Your Favorite Hobbies Or Ways To Spend Time Outside Of Work?

If I’m not in my garage doing woodworking, I’m on a rugby field coaching my two sons’ rugby team.

About Samuel Pasquier

Samuel Pasquier is head of product management for Cisco System’s Industrial IoT Connectivity Portfolio, which is designed to meet IoT needs in manufacturing, oil and gas, utilities, transportation, mining, and the public sector. In this position he oversees the development of the portfolio’s strategic direction, roadmap and investments. Under his leadership the portfolio has achieved 16 consecutive quarters of double-digit revenue growth, increased share in five markets, and doubled its overall revenue.

Competing providers offer a range of features and prices for businesses considering a low-code platform. This article will compare the top nine platforms and explain the features that differentiate them, making it easier to match them to specific needs.

Table Of Contents

• Top Low-Code Platforms
• Low-Code Platforms Comparison Table
  • Best For Visual Modeling: Appian
  • Best For Customization: Claris FileMaker
  • Best For Pre-Built Templates: Studio Creatio
  • Best For Business Intelligence (BI): Microsoft Power Apps
  • Best For Integration: Mendix
  • Best For Deployment Optimization: Outsystems
  • Best For Oracle Database Users: Oracle Application Express (APEX)
  • Best For Analytics And Reporting: Salesforce Lightning
  • Best For User Accessibility: Zoho Creator
• Key Features Of Low-Code Platforms
• How To Choose What Low-Code Platform Is Best For You
• Bottom Line: Top Low-Code Platforms

Top Low-Code Platforms

The top nine low-code platforms all offer feature-rich plans at varying prices. When selecting a provider, match the use cases and costs outlined below to the specific needs for the platform.

Low-Code Platforms Comparison Table

Best Low-Code Platform For Visual Modeling: Appian

Appian is one of the pioneers of the low-code movement and offers users a robust platform that goes beyond basic scripting to build full, complex applications with complete business logic.

Pricing

Appian does not provide pricing information on its website beyond offering a free trial. Contact sales for a quote based.

Features

• Robotic Process Automation (RPA): RPA is used to execute automated actions, responses and processes and is a core part of the platform.
• Complex Business Process Management (BPM): Non-developers can easily build BPM workflows.
• Integrated Developer Environment (IDE): IDE is included, enabling extensibility for custom coding when needed.

Pros

• Strong user management
• Easy for most users
• Strong customer support

Cons

• Limited documentation management
• Difficult to implement
• Limited reporting tools

Best Low-Code Platform For Customization: Claris FileMaker

A division of Apple Inc., Claris FileMaker takes a template-driven approach to help users quickly build data-driven applications. The low-code platform aims to improve the performance of a company’s custom apps, improve scalability with more hosting capacity and protect data for security protocols.

Pricing

Claris FileMaker offers two available pricing plans. The Essentials plan costs $21 per user, per month, billed annually. The standard plan costs $43 per user, per month, billed annually. The vendor offers a 45-day free test drive.

Features

• Graphical User Interface: Claris FileMaker has a graphical user interface for custom application design layouts for any type of device.
• Customizable: Customized workflows are based on job roles.
• Creates Workflows: The drag-and-drop interface makes it easy to build apps and connect different components to create application workflows.

Pros

• Customizable interface
• Multi-user support
• User-friendly database management

Cons

• Limited character count
• Difficult migration
• Limited automation capabilities

Best Low-Code Platform For Pre-Built Templates: Studio Creatio

Formerly known as BPM’online, Creatio is well suited for low-code development of Business Process Management (BPM) applications. Studio Creatio’s pre-built templates provide unlimited customization and give users the ability to create ready-to-use applications.

Pricing

Studio Creatio offers users a free trial of its Studio enterprise plan; the website does not specify how long the free trial lasts. If a company decides to move forward with the plan, it costs $25 per user, per month. Creatio also has a plan for a free Process Designer tool.

Features

• BPM And CRM: Creatio has a strong focus on BPM and Customer Relationship Management (CRM) enablement.
• Artificial Intelligence (AI) Assistance: AI is an embedded part of the platform, providing assistance and direction for low-code application development.
• Pre-made Templates: The template-driven approach with drag and drop interface simplifies application development.

Pros

• Manages marketing plans
• Strong data visualization
• Intuitive and flexible

Cons

• Limited automatic calculations
• Difficult integration
• Limited customization

Best Low-Code Platform For Business Intelligence (BI): Microsoft Power Apps

For businesses already using Microsoft tools, including Power BI (Business Intelligence), Power Apps is an obvious choice for building out low-code tools that leverage the Microsoft platform. Power Apps’ BI features are  especially helpful for building user friendly reports with company data.

Pricing

Microsoft Power Apps offers both subscription and pay-as-you-go plans. The two subscription plans are on a per app basis at $5 per user, per app, per month. The per user plan is $20 per user, per month. The pay-as-you-go plan is $10 per active user, per app, per month.

Features

• Flexible Integration: Power Apps has available integrations including Microsoft’s Power Automate and the Common Data Service which can work seamlessly with Power BI for analytics.
• AI Builder: Template-driven AI models in the AI Builder module enable citizen developers to build complex workflows.
• Customization: Extensibility is a key part of the platform, with the ability to use custom connectors or make use of the Microsoft Azure Functions service.

Pros

• Pre-build formatting
• User friendly
• Strong integration

Cons

• Limited graphical representation
• Complicated licensing
• Limited options to change code

Best Low-Code Platform For Integration: Mendix 

Mendix, a subsidiary of Siemens, is a solid choice for enterprise developers that use SAP software because of the deep partnership between the two firms. Mendix is a helpful choice for those looking for a service that can work with a private cloud deployment as well. Low-code platforms need integration for their data. Mendix provides an integrated collaboration platform to help companies with their development.

Pricing

Mendix offers four plans: free, basic, standard and premium. Basic pricing starts at $60 per month, Standard at $950 per month. For a premium plan, companies should reach out to Mendix’s sales team.

Features

• Integrated Collaboration: As part of the developer portal, integrated collaboration can bring together multiple users to help build low-code applications.
• Multiple Tools: The product’s deep toolset can help with the initial design and goals for a given application.
• AI Assistant: AI assistant helps guide developers on the right actions to take to ensure optical application development and deployment.

Pros

• Scalable
• Flexible development
• Easy visual coding

Cons

• Expensive licenses
• Slow implementation
• Difficult for beginners

Best For Deployment Optimization: Outsystems

The Outsystems platform provides a full workflow and testing capabilities well suited to teams within organizations to build and operate low-code applications. Outsystems assists developers with mobile development, which is a key part of a low-code platform.

Pricing

Outsystems offers three plans. The single-app plan is free. A multiple-app plan starts at $1,513 per month after a free trial. The company also offers a large app portfolio plan; contact sales for a quote.

Features

• Optimized Applications: A key differentiator for Outsystems is its impact analysis, testing and staging platform capabilities, which enable users to build optimized applications.
• Integrated Performance Analysis: The platform’s integrated performance analysis enables users to monitor and improve the performance of applications.
• Strong Deployment: Outsystems generates app code that can run in the Outsystems cloud or any private or public cloud deployment, and provides a simplified approach to package and submit mobile applications to Google Play and the Apple App Store.

Pros

• Intuitive flow editor
• Strong integration
• Flexible platform

Cons

• Expensive platform
• Unreliable management
• Limited customization

Best For Oracle Database Users: Oracle Application Express (APEX)

For organizations already using Oracle’s database and cloud technologies, APEX is an obvious fit, enabling low-code application development for data-driven applications and use cases.

Pricing

Oracle APEX does not list prices online. Users can request a free workspace to try out the platform.

Features

• Charts Data: Charting capabilities for data visualization within apps is an area of differentiation for APEX.
• Unique REST API: Beyond just data applications, APEX enables users to build their own REST APIs that can be used to enable other applications and services.
• Universal Applications: Universal theme user interface development in APEX lets citizen developers easily generate applications that will work across different types of desktop and mobile screens.

Pros

• Simple deployment
• Easy configuration
• Rapid development

Cons

• Limited CSS (Cascading Style Sheets) editing
• Limited documentation
• Oracle Database dependency

Best Low-Code Platform For Analytics And Reporting: Salesforce Lightning

Salesforce Lightning provides a low-code environment as part of the Salesforce Platform. It’s a great option for existing Salesforce CRM users and can also benefit those just looking for an easy-to-use subscription-based service. Salesforce Lightning’s additional tools help companies with analytics and reporting data for app development.

Pricing

Salesforce Lightning has two plans. The Platform Starter plan costs $25 per user, per month, billed annually. The Platform Plus plan costs $100 per user, per month, billed annually. Both plans have a free trial.

Features

• Lightning Flow: Business logic capabilities are built-in via the Lightning Flow feature for BPM.
• Mobile Deployment: All apps built with Salesforce Lighting are by default also enabled for mobile device deployment.
• Salesforce’s Heroku: For more complex application needs, low-code can be complemented with Salesforce’s Heroku Platform-as-a-Service, which provides traditional programming language support.

Pros

• Ability to view the status of sales
• Strong analytic features
• Positive integration

Cons

• Difficult API integration
• Not for beginners
• Limited customization

Best Low-Code Platform For User Accessibility: Zoho Creator

Zoho Creator provides an easy-to-use interface for building both simple and complex applications and can be particularly useful for building multi-device applications. Zoho Creator’s drag-and-drop elements help users easily create apps for iOS and Android.

Pricing

Zoho Creator has many pricing options, all based on an annual subscription. The yearly standard subscription costs $8 per user, per month; the yearly professional subscription costs $20 per user, per month; the yearly enterprise subscription costs $25 per user, per month. A monthly plan is also available, and costs $12-$37 per user, per month, based on features. Zoho also offers a 15-day free trial to test the platform.

Features

• User Access Controls: A key differentiator for Zoho Creator is its well-defined user access controls, which include audit trails as well as single sign-on capabilities.
• Converge Data: The ability to simply converge data from different sources to create a visual dashboard is a core use case.
• Data Integration: Form digitization is another key feature of the platform, with templates that help users to build different types of digital forms that can integrate multiple forms of data including barcodes.

Pros

• Live data tracking
• Simple reporting and analytics
• Workflow and automated notification

Cons

• Limited customization
• Limited documentation
• Difficult search feature

Key Features Of Low-Code Platforms

Low-code platforms help companies by allowing business professionals and IT professionals to collaborate during the coding and application development process. Non-technical professionals can provide insight and business requirements, while IT can look over the coding to help support the development process. This feature saves companies time and increases productivity and efficiency.

Other key features to look for in low-code platforms:

• Pre-Built Templates: The ability to use pre-built templates will benefit companies across their entire infrastructure..
• Drag-and-Drop Interfaces: Drag-and-drop interfaces can simplify development and save time.
• Accessibility: Building an application using low-code can improve accessibility by designing apps that can be accessed on mobile devices, the cloud and on-premises platforms.
• Scalability: A company may be growing while using a low-code platform, and if they are, scalability is necessary to the platform.
• Visual Modeling: Low-code platforms often have visual modeling features and use built-in modules to help anyone understand the platform, whether a beginner or expert developer.

For more information: Trends in Low-Code/No-Code

How To Choose What Low-Code Platform Is Best For You

There are several criteria to consider when evaluating low-code platforms.

Fit For Purpose

As is the case with any development tool, low-code or otherwise, different tools are sometimes optimized for specific use cases and even specific platforms. The first step should be to figure out what the company aims to do with the platform.

Explore Templates 

Many tools provide pre-built templates for different types of applications. Make sure the platform provides what is needed to help accelerate the specific type of development a given project requires.

Extensibility With ‘Full’ Code

While low-code tools can be used to build full applications, there are some capabilities that might require traditional coding extension. If a larger application is the goal, ensure the platform can generate code that can be used in other tools.

Cost And Licensing

Increasingly all forms of software are sold on a subscription model, while some are still sold on more traditional licensed models. Determine which model is the best fit for the use case. It might be more effective to pay for a limited subscription for a small project rather than pay for a lifetime license.

Try It Out

Many platforms offer limited trials. It can be helpful to see how a low-code platform works with specific needs before committing to it.

Bottom Line: Using Low-Code Platforms

When considering providers and solutions of low-code platforms, it’s important to weigh features and cost against a company’s primary goals, including deployment, analytic needs, and customization. While each provider and solution offers a variety of features, identifying a company’s own use case can help better evaluate them against specific needs.

For more information on Low-Code: The Future of Low Code No Code

For those willing to pay, OpenAI makes the tool available on its website for a $20 monthly fee, which also includes priority access to new features as the provider releases them. But other providers offer free ChatGPT-4 access through their own products and services, such as Microsoft’s Bing search engine, for example.

While OpenAI will likely make it fully available to general users in the future, here’s a look in the meantime at how to access the features and functions of ChatGPT-4 for free as well as some of the benefits and disadvantages of using the chatbot technology.

Table Of Contents

• Advantages And Disadvantages Of ChatGPT-4
• How To Use ChatGPT-4 For Free
  • Bing
  • ForeFront AI
  • OpenAI
• Examples of Things ChatGPT-4 Does Well
• Examples of Things ChatGPT-4 Does Not Do Well
• Bottom Line: Using ChatGPT-4

Advantages and Disadvantages of ChatGPT-4

While ChatGPT-4 is a powerful tool that uses advanced technology, it’s still capable of producing factually inaccurate and misleading information. Users need to proceed with caution when relying on the chatbot for use cases where accuracy matters. Here are some of the advantages and disadvantages of using ChatGPT-4.

Advantages

• Availability: ChatGPT-4 is available 24/7 for users who need an immediate response.
• Inexpensive: Free access to the tool puts it within reach of anyone with an internet connection.
• Multilingual: Businesses and users all over the world can use ChatGPT due to its multilingual features. 

Disadvantages

• Misinformation: While OpenAI has improved inaccuracy with the latest release, the nature of the Large Language Model (LLM) that powers the tool means that it is still “learning” with each use through self-analysis and self-correction, and the risk of misinformation or inaccuracy remains high.
• Bias: ChatGPT-4 learns from what users input and what data it is trained on. Because of this, the platform is biased toward those sources. 
• No Emotional Intelligence: Unlike humans, ChatGPT-4 does not factor in emotion when giving advice—something users should keep in mind.

How To Use ChatGPT-4 For Free

How To Use ChatGPT-4 For Free With Bing

1. ChatGPT-4 is only available on Bing when using the latest version of the Microsoft Edge browser. Check for updates before proceeding.
2. On the Bing homepage, click on the “Chat” icon in the top right corner. 
3. Enter any text or input. Emojis, pictures and other media can also be added using the “Attachment” icon at the bottom right corner of the chat box.

How To Use ChatGPT-4 For Free With ForeFront AI

1. ChatGPT-4 is available through the ForeFront AI website to registered users. Account registration is free.
2. On the ForeFront AI website, sign in or create an account.
3. Once logged in, click the GPT box in the top left corner, and select ChatGPT-4.
4. A dropdown box lets users choose or create personas for the tool. The system defaults to “Helpful Assistant,” but other available options include personas in such categories as “Productivity,” “Wellness & Lifestyle,” “History,” “Celebrity,” “Star Wars,” and “Athlete,” among others. Note: These are not real people but personas designed to mimic experts in those subject areas.

4. Users are redirected to the chat page where they can ask questions or add attachments to interact with ChatGPT-4, which will respond as the chosen persona.

How To Use ChatGPT For Free Through OpenAI

1. OpenAI currently only allows free use of an earlier release of the ChatGPT tool, version 3.5, to registered users through its website.
2. Sign in or create an account on the OpenAI site.
3. Click “New Chat” at the top left corner of the page to see examples of how to use the tool as well as its capabilities and limitations.

4. Type a question or prompt into the chat box and press enter to start using ChatGPT.

Examples of Things ChatGPT-4 Does Well

OpenAI designed ChatGPT-4 to be reliable, accurate and capable of handling tasks to benefit users. But it is better at some tasks than others, and before relying on ChatGPT-4, a user or business should know when to use it and when to not.

Code and Provide Coding Assistance

ChatGPT-4 can help users learn to code by automating simple tasks such as file input and output (I/O) operations and database activities. When asked to teach coding, ChatGPT-4 offers advice on how to start, which is especially useful for non-experts wanting to learn simple techniques.

Support Students and Teachers 

ChatGPT-4 can help teachers, professors and students grow their knowledge as well as create study guides, quizzes, tests and lesson plans. From translating languages to answering specific questions, ChatGPT-4 can give more access to educators and students. With the new ability to upload files or pictures to ChatGPT-4, it can also grade simple tests, correct errors and provide feedback to help students better understand what they are learning.

Serve Customers

ChatGPT-4 can handle customer questions and provide assistance across various industries, preventing time wasted on tedious customer service calls and letting employees focus on more difficult tasks. ChatGPT-4 can answer frequently asked questions, provide troubleshooting guidance, and offer general support. 

Generate Content

ChatGPT-4 can generate many different types of creative content, including blog posts, social media updates, product descriptions and song lyrics. It can generate content based on image prompts and up to 25,000 words of text, assisting content creators by offering ideas, creating drafts and editing some writing.

Make Personal Recommendations

ChatGPT-4 can find personalized recommendations and recommend movies or other media. Companies can use Machine Learning (ML) and AI to find the right audience for their advertisements and find new users that might be interested.

Examples of Things ChatGPT-4 Does Not do Well

Whether due to its inaccuracy, inability to contextualize information, or other flaws, ChatGPT-4 is not a reliable source of assistance when it comes to certain tasks. Here are a few to help provide context around when an AI chatbot can be helpful and when it might be better to find another solution.

Provide Personalized or Professional Advice

ChatGPT-4 should not be trusted to offer personalized advice on legal, financial, medical or other matters as a replacement for certified professionals. Consult with a qualified expert instead.

Protect Privacy 

ChatGPT-4 learns from the people who use it, and it may accidentally share other users’ chat histories. This is a privacy concern for any company.

ChatGPT-4 has had many privacy issues, including Samsung’s data leak. Some countries have banned ChatGPT-4 to protect citizens from any data leaks that might occur. Personal and business data should never be shared with ChatGPT-4.

Tell Truth from Fiction

Because of how the LLM works, by trying to understand a user’s prompt and generating strings of words that complete it based on the information upon which it was trained, ChatGPT-4 may provide inaccurate information. OpenAI advises users that the tool “sometimes writes plausible-sounding but incorrect or nonsensical answers,” and it should not be relied upon to provide accurate information unchecked.

Bottom Line: Using ChatGPT-4

ChatGPT has become one of the most well-known AI tools currently accessible for public use, and the latest release is a more efficient, accurate chatbot than any prior versions. OpenAI calls ChatGPT-4 its “most advanced system, producing safer and more useful responses.” Free or inexpensive access to ChatGPT-4 gives more users the ability to benefit from the product for a wide range of uses. While it is easy to use, it is still better at some things than others and users need to remain aware of its limitations around accuracy, reliability and privacy. 

Yasser Alsaied Q&A

How did you first start working in the IoT industry?

For the past six years, I have been involved with the Internet of Things (IoT) from chipsets to System-on-Chip (SoC) to modules to devices and the cloud. I joined Amazon Web Services in 2021 as the vice president of IoT. I lead the AWS IoT business, which covers a wide range of cloud and devices services, such as Robotics, Industrial, Automotive, Consumer, Public Sector and Commercial segments. Our services are among the highest-connected IoT services globally and continue to grow in the fields of digital twins, smart cities and connected vehicles. 

Before joining AWS, I was with Qualcomm as their vice president of IoT as well. During my time at Qualcomm, I held several leadership roles, covering the launch of Qualcomm’s first wireless local-area network (WLAN) chip for mobile phones, Qualcomm Innovation Center, and Code Aurora Foundation to solve legal and operational issues around the open-source software release. During my last four years at Qualcomm, I managed their IoT ecosystem and led the strategy to scale IoT chipsets, including key technologies such as artificial intelligence (AI), computer vision drones, robotics and 5G.

What is your favorite thing about working at AWS?

The most important thing for me is how our work at AWS positively impacts humanity and the environment using IoT technologies. The positive impact and opportunity that AWS offers are unmatched anywhere else.

What sets AWS’s IoT approach or solutions apart from the competition?

It really starts with our market approach to IoT. We understand it is not enough to provide just an IoT platform and disconnected services, and that our customers need fully verticalized, purpose-built solutions that derive actionable insights. They need to be paired with industry partners and account managers that have specialized domain knowledge to reduce complexity of integration and understand customer problems or industry challenges. At AWS, we have created such a deep and broad set of partners, solutions and services, so customers can choose the best solution to drive value for their use case, from secure device connectivity to management, storage, and analytics. Everything runs on the same infrastructure and tools from the cloud to the edge—which ensures seamless performance, reliability, security, scalability, and makes it easier and faster to launch. To support industry verticals, we offer a variety of IoT solution options for the Connected Vehicle, Industrial, Consumer, Public Sector and Commercial markets to best fit the customer’s needs and technical capabilities. 

Another reason AWS is the best place for IoT is our commitment to continuously innovate and make it easier for customers to realize IoT solutions. Since I joined in 2021, AWS IoT has rolled out over 50 updates and launched brand new services, such as AWS IoT FleetWise, AWS IoT ExpressLink, AWS IoT TwinMaker, and AWS IoT RoboRunner. Our qualified device catalog repository has grown over 800 partner devices. 

Lastly, IT and line-of-business customers see security concerns as the top challenge for IoT projects, which limits a business’s ability to move an IoT pilot to production. At AWS, security is the top priority. With all of these services and solutions, AWS is extending the most secure cloud computing environment available today to IoT devices at the edge. Whether they are using AWS IoT managed services, partner solutions, or builder services, customers have access to preventative and active monitoring and response to keep data and devices secure. We also provide a security-dedicated service for IoT devices, AWS IoT Device Defender, which makes it easy to audit configurations, authenticate devices, detect anomalies and receive alerts to help secure your IoT device fleet.

The IoT Industry

What is one key new IoT technology that particularly interests you?

I am keen to focus on the industrial and automotive sectors, as they both seek to promote sustainability and the well-being of humanity and the environment. For example, automation and remote sensing will increase the ability to prevent disasters and know ahead of time if things may go wrong, utilizing AI modeling while protecting equipment and people from running into risky situations.

What is one new IoT technique that teams should implement?

We see a growing need for more simplistic IoT-centric tools. It’s critical to make these tools more accessible for companies to innovate and leverage them, and easier to enter industries as the adoption of IoT technologies continues to grow. For example, tools like AWS IoT Core Device Advisor help developers validate IoT devices for reliable and secure connectivity with AWS. They can identify device software issues, such as being unable to reconnect and get detailed logs to troubleshoot issues during development, and testing cycles.

Another IoT technique that teams should implement is security. As customers move from IoT experimentation and PoCs to deploying IoT production-ready solutions at scale, we find that security is no longer a concern, it’s a barrier to IoT adoption and it’s slowing down digital transformation. Business leaders are excited about the possibilities of IoT, they are also pragmatic about the complexity and security risks associated with deploying IoT solutions. This is due, in part, to a lack of understanding of how to adopt security best practices to the new technologies, as well as a struggle with disparate, incompatible, and sometimes immature security offerings that fail to properly secure deployments, leading to an increased risk. 

AWS IoT’s security strategy is focused on delivering a broad and deep set of security capabilities that allow customers to keep their devices and infrastructure secure with multi-layered protection from edge-to-cloud—protecting their IoT devices, their connectivity, and the data that they generate.

What is one new IoT strategy that companies should implement?

We continue to see very strong IoT interest and adoption from our customers. We don’t anticipate IoT growth will slow down any time soon. However, it is clear that the role of IoT hyperscalers is changing, and in large part, this is tied to an industry shift towards verticalized solutions instead of IoT as a horizontal offering. This shift is in the best interest of customers because they never come to us asking for IoT directly. Instead, they come to us seeking specific business outcomes and for help determining how they can leverage technology to monitor, control, and optimize their business processes to get those outcomes. What this shift means for cloud and IoT software providers is they must put IoT into context for customers’ unique vertical challenges by offering industry-focused solutions and partners that drive business value based on their customer’s in-house skillset, IT scale requirements and use cases. 

In addition, it is becoming more important for companies to work with partners to build complete IoT solutions and applications together. It is vital to ensure companies and their partners are building and creating solutions that are deployed quickly to realize business outcomes and accelerate their time to value. This is also another key strategy companies should implement.

What is the biggest IoT mistake you see enterprises making?

IoT can become complex, and not all companies grasp it. But companies are starting to understand the incredible value of collecting available data, especially in manufacturing, automotive, and enterprise verticals. Data is critical for companies that need to monitor, protect, and improve their products and services. Therefore, the biggest challenge is misunderstanding the value of IoT data and not looking at them as valuable sources to help improve the environment or challenges that companies face today.

In addition, we heard from our customers about the other common areas where they struggle with IoT. For example, they need to navigate the breadth of technologies and skills required for the ecosystem. They also encounter challenges related to adoption, scaling, and device management. For instance, they often need help connecting legacy equipment that wasn’t designed for digitization, or guidance on how to connect digitized OT with IT backend quickly and cost-effectively. Finally, customers also have concerns with future-proofing investments. They have to consider how IoT investments will impact existing infrastructure, drive ROI or incur technical debt in the future.

What are some promising current trends in the IoT market?

Customers are broadening their sustainability initiatives to go beyond emission reduction to create smart environments (i.e. cities, buildings, factories), leveraging IoT to monitor energy performance, reduce waste, and align facility operations with occupancy trends. One great example of this is how Yara collaborated with us to build an efficient and sustainable Digital Production Platform (DPP) for the farming industry. This DPP is a key enabler to digitize their production system across 28 production sites, 122 production units, and two mines. The DPP detects, collects, and runs sophisticated analytics on production data linked to productivity, reliability, environment, safety, quality, and innovation, using AWS IoT SiteWise, AWS IoT Greengrass, AWS IoT Core, AWS IoT Analytics, and Amazon SageMaker. This solution has helped Yara to predict product quality and composition, improve balancing of the site utilities and detect when machines need repair or maintenance to keep production at optimal efficiency levels.

At AWS, we’ve made the consumer-centric vertical approach the north star of our IoT strategy. To better serve our customers, we’ve verticalized our IoT and AI services in ways that are optimized to deliver accelerated outcomes for segment-specific use cases. For instance, AWS IoT SiteWise and AWS IoT TwinMaker services were built to support Industrial IoT customers with collecting, organizing, and analyzing industrial data, as well as creating digital twins of real-world industrial environments. AWS IoT FleetWise supports our automotive customers. We also work with vertically-focused partners who use these services to build solutions for our customers. Our IoT products, sales, and support resources have been restructured to align with key customer industries, allowing us to be more customer obsessed and streamlined in our ability to address customer needs and challenges.

At AWS, we consider the cost implications of every service and feature we design and across our offerings such as compute, storage, and databases—the foundational building blocks for every IT system and application—AWS continuously works to help customers improve performance while lowering their costs. As the impacts of the challenging macroeconomic environment continue, we are seeing customers more focused on controlling costs, and we are actively helping customers optimize cloud spending for existing workloads. In fact, one of the benefits of the cloud compared to managing a data center is the ability to optimize costs relatively quickly. For example, when it comes to IoT, we are providing edge processing and connectivity capabilities through FreeRTOS, AWS IoT ExpressLink and AWS IoT Greengrass, thus enabling customers to analyze data closer to where it is being captured and optimizing their cloud-related expenses.

What are the biggest factors that are driving change in IoT?

The technology that is traditionally referred to as IoT has advanced hugely in recent years. We are rapidly evolving towards a new paradigm of hybrid edge, cloud-connected architectures that achieve much more than just collecting and sharing data. I believe this is one of the factors that is driving the change in IoT. Our commitment to making IoT solutions more accessible globally ties directly into our continued efforts to expand our hybrid cloud and edge computing capabilities. By extending our AWS infrastructure, services, application programming interfaces (APIs), and tools to edge locations like on-premises data centers, 5G towers, and smart factories, we are able to provide all the benefits of the cloud for workloads that require low latency, data residency, local data processing, or complex application interdependencies. 

How has IoT changed during your time in the market?

Over the last decade, IoT has grown from aspirational technology, such as simple task machines to a core differentiator that businesses use to solve problems and drive value through revenue generation, operational improvements, and innovation. For example, more and more companies deploy IoT devices and use them to support critical use cases. Companies have transitioned from “Why do we need to invest in IoT” to “How can we scale IoT deployments more efficiently.” During this period, customers had to go through their internal alignment to bring IT and OT teams together. Now, we see those who embarked on the IoT journey early on reaping the benefits of it with new business value. Take the case of Autodesk, which has built a whole range of IoT services around its Info360 platform for water utilities. Using AWS IoT as the basis of their platform design, they have reduced their technical debt and development time by 60 percent.

We have also seen customers needing help to create scalable architectures where they can easily connect a range of devices, collect data, and analyze it to make informed decisions. These customers have relied on AWS and AWS Partners to simplify their IoT journey by offering a deep, broad, and secure set of solutions and services. Continuing to reduce initial costs and complexities has proven to help customers get the most out of their IoT vision. For instance, Dexatek Technology, a Taiwanese company that gives electronic consumer products smart capabilities using its IoT solutions, increased the performance of its IoT platform, enhanced security, and lowered management time by migrating to AWS IoT Core.

Where do you predict the IoT market will be five or 10 years from now?

I believe IoT will become a universal business expectation rather than an exception, and the growth of IoT will continue with connected enterprises and factories. Many businesses and industries will continue to invest in IoT because it provides business and operational value and they want to connect to the cloud for scalability and benefit from infrastructure cost savings. Companies will also continue investing in IoT technologies and other relevant rising trends, such as generative AI, AI/ML applications. As a result, we will continue to see new customer segments unlocking the value of IoT. 

New data analytics patterns will also be unlocked in the future as more and more IoT sensors come online. These sensors will be capable of capturing new information with high accuracy, such as new analytics in software-defined vehicles or factories of the future with Industry 4.0 initiatives. Companies will look to IoT leaders like AWS to provide more verticalized solutions that are easy to deploy and repurpose across multiple instances. AWS IoT has already embarked on such a direction by offering industry-specific verticalized services, such as AWS IoT SiteWise, AWS IoT TwinMaker, AWS IoT FleetWise, AWS IoT RoboRunner, and AWS IoT ExpressLink. In the coming years, it will be critical to make IoT-centric and solution-based tools more accessible for companies to innovate and leverage them, allowing them to more easily enter the industry as the adoption of IoT technologies continues to grow.

Personnel in IoT

What is one new IoT development your team wants professionals to know?

One of the IoT developments that professionals should know about is the services built to collect, manage, and visualize data from industrial equipment sources at the edge. For example, AWS IoT SiteWise is built to enable industrial enterprises to collect, store, organize, and visualize thousands of sensor data streams across multiple industrial facilities. This will become an important technology to help industrial companies as IoT is becoming increasingly critical.

If you could give one piece of advice to an IoT professional at the beginning of their career, what would it be?

Be cautious about operational excellence and security, two critical success factors for the IoT business. The scale and growth of IoT have a large radius; therefore, IoT professionals need to understand how to securely design, build and scale IoT technologies that can withstand these requirements.

With the shortage of tech talent, how is your team finding and retaining professionals to work in IoT?

The IoT business has always been a team sport. Whether companies are working with their own teams or partners, when there is a shortage in certain areas, they should look for partners to find the right solutions to help solve customer challenges. The goal is to ensure customers are up and running securely and at scale.

For the greatest business impact, what should IoT professionals be focusing on most in their roles?

One of our leadership principles is customer obsession. We start with the customer and work backward to earn and keep their trust. Therefore, delivering results and bringing value (e.g., helping customers to optimize costs when using our services or reducing energy consumption and waste by utilizing the data from IoT devices) to the customer is the bottom line that IoT professionals should focus on most in their roles.

Work-Life

What is one of your top professional accomplishments?

One of my top professional accomplishments was developing and opening up an ecosystem for OEM partners to build smartphones more easily when I worked at Qualcomm. Also, at AWS, I am pleased to work closely with some of the chip providers in the industry, such as Arm, NXP Semiconductors, Intel, Qualcomm, and others to integrate cloud services in their product design and bridge the gap between HW and SW for IoT applications.

What is your favorite part of working in the IoT market?

I truly believe in the transformative power of IoT and its ability to drive innovation, create new business models, and improve lives. Meeting and getting to know the people and experts within the IoT industry, from small businesses to large, open-minded enterprises, is important for me. I enjoy connecting with IoT professionals to learn more about their visions and innovations.

What is one of your favorite parts of the workweek? How does it encourage or inspire you?

Investing in our people is important for me. I enjoy talking to new and upcoming engineers and junior staff, our customers, and partners, hearing and understanding their big picture and thoughts about the IoT industry. I strongly believe that by working together, we can push the boundaries of what is possible in IoT and deliver innovative solutions that make a real difference and impact in the world.

Do you have a favorite way to recharge during the workday?

Connecting with people around me and keeping in touch with family and friends keeps me going during the workday. I love hearing stories and how those impact our lives and the environment surrounding us, starting with family members and extending to people I work or interact with.

What are your favorite hobbies or ways to spend time outside of work?

Outside work, I like to cook and spend time with my family and friends. I also enjoy car racing in my leisure time.

About Yasser Alsaied

Alsaied leads Amazon Web Services (AWS) IoT business, which includes IoT Core, Industrial, Automotive and IoT devices. His group’s services are among the highest-connected IoT services globally and continue to grow in the fields of digital twins, smart cities, and connected smart vehicles. He joined AWS from Qualcomm, where he was vice president of IoT and held various leadership roles, including managing teams that released Qualcomm’s first Wireless Local Area Network (WLAN) chip for mobile phones and leading the formation and launch of the Qualcomm Innovation Center (QuIC) and Code Aurora Foundation (CAF) to solve legal and operational issues around the open-source software release. 

For the past four years, Alsaied managed Qualcomm’s IoT ecosystem. He directly managed the critical part of the strategy to scale IoT chipsets, including key technologies such as artificial intelligence (AI), computer vision drones, robotics, and 5G. In later years, Alsaied was involved in developing a network application vehicle in Nortel Networks that provided advanced speech recognition technology. Alsaied was then part of the Nortel research team to develop 3G architecture and participated in the location-based services and payment processes on 3G. The years following Nortel were spent holding major leadership roles in Philips, ATI, and AMD. He was part of their respective consumer electronic business units and played key roles in design wins that implemented leading-edge technologies in consumer products with very large volumes.

As businesses discover new use cases and develop the infrastructure to support more IoT applications, the entire Internet of Things continues to evolve. Let’s look at some of the current trends in that evolution.

Table Of Contents

• Top 5 IoT Trends
  1. IoT Cybersecurity Concerns Grow
  2. IoT Advancements In Health Care
  3. 5G Enables More IoT Opportunities
  4. Demand For Specialized IoT Data Management
  5. Bundled IoT For The Enterprise Buyer
• The Future Of IoT
• Bottom Line: IoT Trends

Top 5 IoT Trends

IoT devices can help companies use their data in many ways, including generating, sharing and collecting data throughout their infrastructure. While some companies are leaping into IoT technology, others are more cautious, observing from the sidelines to learn from the experiences of those pioneering IoT.

When looking through these five key trends, keep in mind how IoT devices affect and interact with company infrastructure to solve problems.

1. IoT Cybersecurity Concerns Grow

As new IoT solutions develop quickly, are users being protected from cyber threats and their connected devices? Gabriel Aguiar Noury, robotics product manager at Canonical, which publishes the Ubuntu operating system, believes that as more people gain access to IoT devices and the attack surface grows, IoT companies themselves will need to take responsibility for cybersecurity efforts upfront.

“The IoT market is in a defining stage,” Noury said. “People have adopted more and more IoT devices and connected them to the internet.” At the same time they’re downloading mobile apps to control them while providing passwords and sensitive data without a clear understanding of where they will be stored and how they will be protected—and, in many cases, without even reading the terms and conditions.

“And even more importantly, they’re using devices without checking if they are getting security updates…,” Noury said. “People are not thinking enough about security risks, so it is up to the IoT companies themselves to take control of the situation.”

Ben Goodman, SVP of global business and corporate development at ForgeRock, an access management and identity cloud provider, thinks it’s important that we start thinking of IoT devices as citizens and hold them accountable for the same security and authorization requirements as humans.

“The evolution of IoT security is an increasingly important area to watch,” Goodman said. “Security can no longer be an afterthought prioritized somewhere after connectivity and analytics in the Internet of Things. Organizations need to start treating the ‘things’ in the Internet of Things as first-class citizens.”

Goodman said such a measure would mean that non-human entities are required to register and authenticate and have access granted and revoked, just like humans, helping to ensure oversight and control.

“Doing this for a thing is a unique challenge, because it can’t enter a username or password, answer timely questions, or think for itself,” he said. “However, it represents an incredible opportunity to build a secure network of non-human entities working together securely.”

For more information on IoT and security: Internet of Things (IoT) Security Trends

2. IoT Advancements In Healthcare

The healthcare industry has benefited directly from IoT advancements. Whether it’s support for at-home patient care, medical transportation, or pharmaceutical access, IoT solutions are assisting healthcare professionals with more direct care in situations where they cannot provide affordable or safe hands-on care.

Leon Godwin, principal cloud evangelist for EMEA at Sungard AS, a digital transformation and recovery company, explained that IoT not only makes healthcare more affordable—it also makes care and treatment more accessible and patient-oriented.

“IoT in healthcare will become more prevalent as healthcare providers look to reduce costs and drive better customer experience and engagement,” Godwin said. “This might include advanced sensors that can use light to measure blood pressure, which could be incorporated in watches, smartphones, or standalone devices or apps that can measure caloric intake from smartphone cameras.”

Godwin said that AI is also being used to analyze patient data, genetic information, and blood samples to create new drugs, and after the first experiment using drones to deliver organ transplants across cities happened successfully, rollout is expected more widely.

Jahangir Mohammed, founder and CEO of Twin Health, a digital twin company, thinks that one of the most significant breakthroughs for healthcare and IoT is the ability to constantly monitor health metrics outside of appointments and traditional medical tests.

“Recent innovations in IoT technology are enabling revolutionary advancements in healthcare,” Mohammed said. “Until now, individual health data has been mostly captured at points in time, such as during occasional physician visits or blood labs. As an industry, we lacked the ability to track continuous health data at the individual level at scale.

“Advancements in IoT are shifting this paradigm. Innovations in sensors now make it possible for valuable health information to be continuously collected from individuals.

Mohammed said advancements in AI and Machine Learning, such as digital twin technology and recurrent neural networks, make it possible to conduct real-time analysis and see cause-and-effect relationships within incredibly complex systems.

Neal Shah, CEO of CareYaya, an elder care tech startup, cited a more specific use case for IoT as it relates to supporting elders living at home—a group that suffered from isolation and lack of support during the pandemic.

“I see a lot of trends emerging in IoT innovation for the elderly to live longer at home and avoid institutionalization into a nursing home or assisted living facility,” Shah said. Through research partnerships with university biomedical engineering programs, CareYaya is field testing IoT sensors and devices that help with everything from fall prevention to medication reminders, biometric monitoring of heart rate and blood pressure—even mental health and depression early warning systems through observing trends in wake-up times.

Shah said such IoT innovations will improve safety and monitoring and make it possible for more of the vulnerable elderly population to remain in their own homes instead of moving into assisted living.

For more information on health care in IoT: The Internet of Things (IoT) in Health Care

3. 5G Enables More IoT Opportunities

5G connectivity will make more widespread IoT access possible. Currently, cellular companies and other enterprises are working to make 5G technology available in more areas to support further IoT development.

Bjorn Andersson, senior director of global IoT marketing at Hitachi Vantara, a top-performing IoT and  IT service management company, explained why the next wave of wider 5G access will make all the difference for new IoT use cases and efficiencies.

“With commercial 5G networks already live worldwide, the next wave of 5G expansion will allow organizations to digitize with more mobility, flexibility, reliability, and security,” Andersson said. “Manufacturing plants today must often hardwire all their machines, as Wi-Fi lacks the necessary reliability, bandwidth, or security.”

But 5G delivers the best of two worlds, he said—the flexibility of wireless with the reliability, performance, and security of wired networks. 5G provides enough bandwidth and low latency to have a more flexible impact than a wired network, enabling a whole new set of use cases.

Andersson said 5G will increase the feasibility of distributing massive numbers of small devices that in the aggregate provide enormous value with each bit of data.

“This capacity to rapidly support new apps is happening so early in the deployment cycle that new technologies and infrastructure deployment can happen almost immediately, rather than after decades of soaking it in,” he said. “With its widespread applicability, it will be feasible to deliver 5G even to rural areas and remote facilities far more quickly than with previous Gs.”

For more: Internet of Things (IoT) Software Trends

4. Demand For Specialized IoT Data Management

With its real-time collection of thousands of data points, the IoT solutions strategy focuses heavily on managing metadata about products and services. But the overwhelming amount of data involved means not all IoT developers and users have begun to fully optimize the data they can now access.

Sam Dillard, senior product manager of IoT and edge at InfluxData, a data platform provider for IoT and in-depth analytics use cases, believes that as connected IoT devices expand globally, tech companies will need to find smarter ways to store, manage and analyze the data produced by the Internet of Things.

“All IoT devices generate time-stamped (or time series) data,” Dillard said. “The explosion of this type of data, fueled by the need for more analytics, has accelerated the demand for specialized IoT platforms.”

By 2025, around 60 billion connected devices are projected to be deployed worldwide—the vast majority of which will be connected to IoT platforms, he said. Organizations will have to figure out ways to store the data and make it all sync together seamlessly as IoT deployments continue to scale at a rapid pace.

5. Bundled IoT For The Enterprise Buyer

While the average enterprise buyer might be interested in investing in IoT technology, the initial learning curve can be challenging as IoT developers work to perfect new use cases for users.

Andrew De La Torre, group VP of technology for Oracle Communications at cloud and data management company Oracle, believes that the next big wave of IoT adoption will be in bundled IoT or off-the-shelf IoT solutions that offer user-friendly operational functions and embedded analytics.

Results of a survey of 800 respondents revealed an evolution of priorities in IoT adoption across industries, De La Torre said—most notably, that enterprises are investing in off-the-shelf IoT solutions with a strong desire for connectivity and analytics capabilities built-in.

Because of specific capabilities, commercial off-the-shelf products can extend IoT into other industries thanks to its availability in public marketplaces. When off-the-shelf IoT aligns with industrial needs, it can replace certain components and systems used for general-use practices.

While off-the-shelf IoT is helpful to many companies, there are still risks as it develops—security risks include solution integration, remote accessibility and widespread deployments and usage. Companies using off-the-shelf products should improve security by ensuring that systems are properly integrated, running security assessments, and implementing policies and procedures for acquisitions.

The Future Of IoT

Customer demand changes constantly. IoT services need to develop at the same pace.

Here’s what experts expect the future of Iot development to look like:

Sustainability and IoT

Companies must embrace IoT and its insights so they can pivot to more sustainable practices, using resources responsibly and organizing processes to reduce waste.

There are multiple ways a company can contribute to sustainability in IoT:

• Smart energy management: Using granular IoT sensor data to allow equipment control can eliminate office HVAC system waste and benefit companies financially and with better sustainability practices.
• Extent use style: Using predictive maintenance with IoT can extend the lifespan of a company’s model of manufacturing. IoT will track what needs to be adjusted instead of creating a new model.
• Reusing company assets: Improved IoT information will help a company determine whether it needs a new product by looking at the condition of the assets and use history.

IoT and AI

The combination of Artificial Intelligence (AI) and IoT can cause industries, businesses and economies to function in different ways than either IoT or AI function on their own. The combination of AI and IoT creates machines that have smart behaviors and supports strong decision-making processes.

While IoT deals with devices interacting through the internet, AI works with Machine Learning (ML) to help devices learn from their data.

AI IoT succeeds in the following implementations:

• Managing, analyzing, and obtaining helpful insights from customer data
• Offering quick and accurate analysis
• Adding personalization with data privacy
• Providing assistance to use security against cyber attacks

More Use of IoT in Industries

Healthcare is cited as one of the top IoT industries, but many others are discovering how IoT can benefit their companies.

Agriculture

IoT can be used by farmers to help make informed decisions using agriculture drones to map, image, and survey their farms along with greenhouse automation, monitoring of climate conditions, and cattle monitoring.

IoT enables agriculture companies to have more control over their internal processes while lowering production risks and costs. This will reduce food waste and improve product distribution.

Energy

IoT in the energy sector can improve business performance and customer satisfaction. There are many IoT benefits for energy industry, especially in the following areas:

• Remote monitoring and managing
• Process optimization
• Workload forecasting
• Grid balancing
• Better decision-making

Finance

Banks and customers have become familiar with managing transactions through many connected devices. Because the amount of data transferred and collected is extensive, financial businesses now have the ability to measure risk accurately using IoT.

Banks will start using sensors and data analytics to collect information about customers and offer personalized services based on their activity patterns. Banks will then better understand how their customers handle their money.

Manufacturing

Manufacturing organizations gather data at most stages of the manufacturing process, from product and process assistance through planning, assembly and maintenance.

The IoT applications in the manufacturing industry include:

• Production monitoring: With IoT services’ ability to monitor data patterns, IoT monitoring provides optimization, waste reduction and less mundane work in process inventory.
• Remote equipment management: Remote work has grown in popularity, and IoT services allow tracking and maintaining of equipment’s performance.
• Maintenance notifications: IoT services help optimize machine availability by receiving maintenance notifications when necessary.
• Supply chains: IoT solutions can help manufacturing companies track vehicles and assets, improving manufacturing and supply chain efficiency.

For more industries using IoT: IoT in Smart Cities

Bottom Line: IoT Trends

IoT technology reflects current trends and reaches many areas including AI, security, healthcare, and other industries to improve their processes.

Acknowledging IoT in a business can help a company improve a company structure, and IoT will benefit a company’s infrastructure and applications.

For IoT devices: 85 Top IoT Devices

Big Data security is routed through a circuitous path, and in theory could be vulnerable at more than one point. 

Navigating Big Data Security & Trends

Two of the biggest trends in the world of big data stand somewhat in opposition to each other: the proliferation of big data that informs smart technology, and also the growing movement for consumers to own and decide how their personal data is being used.

Technologies like IoT, artificial intelligence, machine learning, and even customer relationship management (CRM) databases collect terabytes of data that contain highly sensitive personal information. This personal form of big data is valuable for enterprises that want to better cater their products and services to their audience, but it also means that all companies and third-party vendors are held responsible for the ethical use and management of personal data.

As big data and its enterprise use cases continue to grow, most organizations work hard to comply with consumer data laws and regulations, but their security holes leave data vulnerable to breach. Take a look at some of the top trends happening in the big data world, the important security points that many companies are missing, and some tips for getting big data security right:

Update your cloud and distributed security infrastructure

Big data growth has caused many companies to move toward cloud and data fabric infrastructures that allow for more data storage scalability. The problem? Cloud security is often established based on legacy security principles, and as a result, cloud security features are misconfigured and open to attack.

For a company to navigate this requires speaking with cloud and storage vendors about their products, whether a security solution is embedded, and if they or a third-party partner recommend any additional security resources. 

Set mobile device management policies and procedures

IoT and other mobile devices are some of the greatest sources and receivers of big data, but they also offer several security vulnerabilities since so many of these technologies are owned and used for personal life. Set strict policies for how employees can engage with corporate data on personal devices, and be sure to set additional layers of security in order to manage which devices can access sensitive data.

Provide data security training and best practices

Most often, big data is compromised as the result of a successful phishing attack or other personalized attack targeted at an unknowing employee. Train your employees on typical socially engineered attacks and what they look like, and again, set up several layers of authentication security to limit who can access sensitive data storage.

For more big data trends: Big Data Trends and The Future of Big Data

Benefits Of Big Data Security

With the benefits of customer retention, risk identification, business innovation, cost, and efficiency, a big data security system can be of value to companies everywhere. 

Here are key benefits of big data security:

• Customer Retention: With big data security, a company can observe many data patterns, which allows them to better fit their products and services with their clients needs. 
• Risk Identification: Because of big data security, a company can use big data tools to identify risks in their infrastructure, helping companies create a risk management solution.
• Business Innovation: Big data security can help companies update their tools and help transfer products into new secure systems. This innovation can improve business processes, marketing techniques, customer service, and company productivity.
• Cost Optimization: Big data security technologies can reduce customer costs by efficiently storing, processing, and analyzing large volumes of data. Big data security tools also will calculate how the product will benefit the company, so companies can pick a company that is better for their infrastructure.

For more information on data management: 5 Top Data Management Predictions

Challenges of Big Data Security

There are several challenges to securing big data that can compromise its security. Keep in mind that these challenges are by no means limited to on-premise big data platforms. They also pertain to the cloud. When you host your big data platform in the cloud, take nothing for granted. Work closely with your provider to overcome these same challenges with strong security service level agreements.

Here are the key challenges to big data security:

• Newer technologies can be vulnerable: Advanced analytic tools for unstructured big data and nonrelational databases (NoSQL) are examples of newer big data technologies in active development. It can be difficult for security software and processes to protect these new toolsets.
• Variable impact: Mature security tools effectively protect data ingress and storage. However, they may not have the same impact on data output from multiple analytics tools to multiple locations.
• Access without permission: Big data administrators may decide to mine data without permission or notification. Whether the motivation is curiosity or criminal profit, your security tools need to monitor and alert on suspicious access no matter where it comes from.
• Beyond routine audits: The sheer size of a big data installation, terabytes to petabytes large, is too big for routine security audits. And because most big data platforms are cluster-based, this introduces multiple vulnerabilities across multiple nodes and servers.
• Requires constant updates: If the big data owner does not regularly update security for the environment, they are at risk of data loss and exposure.

Big Data Security Technologies

None of these big data security tools are new, from encryption to user access control. What is new is their scalability and the ability to secure multiple types of data in different stages.

• Encryption: Your encryption tools need to secure data in transit and at rest, and they need to do it across massive data volumes. Encryption also needs to operate on many different types of data, both user- and machine-generated. Encryption tools also need to work with different analytics toolsets and their output data, and on common big data storage formats including relational database management systems (RDBMS), non-relational databases like NoSQL, and specialized filesystems such as Hadoop Distributed File System (HDFS).
• Centralized Key Management: Centralized key management has been a security best practice for many years. It applies just as strongly in big data environments, especially those with wide geographical distribution. Best practices include policy-driven automation, logging, on-demand key delivery, and abstracting key management from key usage.
• User Access Control: User access control may be the most basic network security tool, but many companies practice minimal control because the management overhead can be so high. This is dangerous enough at the network level and can be disastrous for the big data platform. Strong user access control requires a policy-based approach that automates access based on user and role-based settings. Policy-driven automation manages complex user control levels, such as multiple administrator settings that protect the big data platform against inside attacks.
• Intrusion Detection and Prevention: Intrusion detection and prevention systems are security workhorses. This does not make them any less valuable to the big data platform. Big data’s value and distributed architecture lend themselves to intrusion attempts. IPS enables security admins to protect the big data platform from intrusion, and should an intrusion succeed, IDS quarantines the intrusion before it does significant damage.
• Physical Security: Don’t ignore physical security. Build it in when you deploy your big data platform in your own data center or carefully do due diligence around your cloud provider’s data center security. Physical security systems can deny data center access to strangers or to staff members who have no business being in sensitive areas. Video surveillance and security logs will do the same.

Also read: How Big Data is Used: Business Case Studies

Implementing Big Data Security

Whether you’re just getting started with big data management and are looking for initial big data security solutions, or you are a longtime big data user and need updated security, here are a few tips for big data security implementation:

• Manage and train internal users well: As alluded to before, accidental security mistakes by employees offer one of the most frequently used security vulnerabilities to malicious actors. Train your employees on security and credential management best practices, establish and have all users sign mobile and company device policies, and offer only minimum-necessary data source access to each user based on their role.
• Plan regular security monitoring and audits: Especially in larger companies where big data and software grows on a near-daily basis, it’s important to regularly assess how the network and data landscape changes over time. Several network monitoring tools and third-party services are offered on the market, giving your security staff real-time visibility into unusual activity and users. Regular security audits also give your team the opportunity to assess bigger-picture issues before they become true security problems.
• Talk to a trusted big data company: Big data storage, analytics, and managed services providers usually offer some form of security or partner with a third-party organization that does. The platform that you use might not have all of the specific features that your industry or particular use cases require, so talk to your providers about your security concerns, regulatory requirements, and big data use cases so they can customize their services to what you need.

More on security implementation: Top 10 Ways to Prevent Cyber Attacks

Who Is Responsible For Big Data Security?

A big data deployment crosses multiple business units. IT, database administrators, programmers, quality testers, InfoSec, compliance officers, and business units are all responsible in some way for the big data deployment. Who is responsible for securing big data?

The answer is everyone. IT and InfoSec are responsible for policies, procedures, and security software that effectively protect the big data deployment against malware and unauthorized user access. Compliance officers must work closely with this team to protect compliance, such as automatically stripping credit card numbers from results sent to a quality control team. DBAs should work closely with IT and InfoSec to safeguard their databases.

Finally, end-users are just as responsible for protecting company data. Ironically, even though many companies use their big data platform to detect intrusion anomalies, that big data platform is just as vulnerable to malware and intrusion as any stored data. One of the simplest ways for attackers to infiltrate networks, including big data platforms, is a simple email. Although most users will know to delete the usual awkward attempts from Nigerian princes and fake FedEx shipments, some phishing attacks are extremely sophisticated. When an admin is administering security for the company big data platform, never ignore the power of a lowly email.

Secure your big data platform from high threats and low, and it will serve your business well for many years.

Read next: Top 10 Cybersecurity Threats

Big Data Security Companies

Digital security is a huge field with thousands of vendors. Big data security is a considerably smaller sector given its high technical challenges and scalability requirements. However, big data owners are willing and able to spend money to secure valuable employments, and vendors are responding. Below are a few representative big data security companies.

Snowflake

Snowflake’s team of data experts believe that data security should be natively built into all data management systems, rather than added on as an afterthought. Snowflake’s Data Cloud includes comprehensive data security features like data masking and end-to-end encryption for data in transit and at rest. They also offer accessible support to their users, allowing them to submit reports that Snowflake and their partner, HackerOne, can analyze while running their private bug program.

Teradata

Teradata is a top provider of database and analytics software, but they’re also a major proponent and provider of cloud data security solutions. Their managed service, called Cloud Data Security As-a-Service, offers regular third-party audits to prepare for data regulatory committee audits. They also offer features such as data encryption in transit and at rest, database user role management, storage device decommissioning, cloud security monitoring, and a two-tiered cloud security defense plan.

Cloudera

Cloudera’s primary strategy for big data security is to consolidate security management through their shared data experience (SDX), or to manage security and policies from a unified standpoint across all workloads. This means that even as tools and most frequently used workloads change over time, policy and security updates can still be managed centrally without siloes. Among their security solutions, Cloudera provides unified authentication and authorization, end-to-end visibility for audits, security solutions, data policy-specific solutions, and several forms of encryption.   

IBM

IBM’s data security portfolio focuses on multiple environments, global data regulations, and simple solutions so that users can easily manage their data sources and security updates after deployment. Some of the main areas that IBM pays attention to for data security include hybrid cloud security management, embedded policy and regulation management, and secure open source analytics management. 

Oracle

Oracle is one of the largest database hosts and providers in the big data market, but they also offer several top-tier security tools to their customers. Their security solutions focus on the following categories: security assessment, data protection and access control, and auditing and monitoring They also extend platform-specific security support for two of their most popular solutions, Autonomous Database and Exadata.

Hear from a Big Data Exec at Teradata: Ask an Executive: Data Analytics in Business

Bottom Line: Big Data Security

If a company uses well chosen big data security tools, these tools will serve the business well for many years, enabling it to secure its big data platform from threats of all kinds. 

The cloud networking market has made it easier for companies to use intent-based networking, business intelligence (BI), configuration management, and services such as software-defined, cloud, edge, and networking solutions.

For more network trends: Top Network Segmentation Trends

Top 5 Cloud Networking Trends

1. Enterprise Network Strategy In The User’s Home

Changing workforce expectations have led many companies to a more globally distributed remote workforce – a trend that also rises with the cloud. 

As a result, enterprise networking infrastructure now has to support users in their homes.

Drit Suljoti, co-founder and CTO of Catchpoint, a digital experience monitoring platform provider, explained that consumer-grade networking technology does not always offer the levels of support and visibility necessary for remote work, which is increasingly becoming a problem.

“Organizations across the board have experienced the frustrations and performance volatility that can result from consumer-grade WiFi, VPN clients, and increased dependence on the internet from the employee’s wider household,” Suljoti said. “At the ground level, how can IT support desks ensure they have the necessary visibility into the daily digital life of their remote employees? 

“These mission-critical teams need the ability to understand the digital performance of an individual’s device, network, and applications, and the third-party providers they rely on. This is even more essential when employees are working remotely, without on-site support to troubleshoot performance issues.”

Bob Friday, VP and CTO of Mist, Juniper’s artificial intelligence (AI)-driven enterprise business, believes that many companies are starting to respond to this remote work shift by increasing networking security and monitoring their employees’ remote work environments.

“[A] major shift is in how enterprise-level networking trends are becoming increasingly important for personal users as well,” Friday said. “Whether you’re an executive at a company or you work in a profession that puts you into contact with sensitive information, the continued normalization of remote and hybrid work environments means that enterprise-grade networking and security will move into the home networking space.

“To ensure end-to-end network visibility, reliability, and security, we can expect enterprise-grade networking solutions to begin permeating remote and hybrid workforces, as enterprise IT teams take an even sharper look at their network edge.”

2. Networking With Remote AI Support

Users and enterprise devices often need technical support that was normally provided in the office. As remote work – again, supported by the cloud – continues to become a standard approach, many companies are adopting AI solutions to assist with customer experience (CX) and support requirements of the network.

“More help is needed in managing this critical infrastructure, which is why AI has become a necessity for network management,” said Friday. “Enterprises and technology providers have already adopted AI assistants in their networking support teams. Cloud AI has enabled a new tech support model, one that has created the volume and quality of data necessary to train AI technologies. 

“This AIOps model has led to incredible progress. At present, AI can answer up to 70% of support tickets with the same effectiveness as a domain expert. Eventually, this AIOps technology will move all the way to the end-user. 

“And like the average human employee, AI has the ability to learn and improve over time, thus providing a better customer experience consistently and proactively. But unlike the average human employee, that skill and expertise is not lost when they retire or quit. The more that AI is used as part of the IT help desk, the more the technology can improve its answers and, ultimately, the end-user experience.”

3. The Growth Of Intent-Based Networking (IBN)

Networking technology continues to grow more sophisticated. Particularly with the more widespread use of software-defined networking (SDN), intent-based networking is being used more in enterprise networks that want additional business intelligence (BI), configuration management, and other features embedded in their networks. All of these feature are part of the growing sophistication of cloud technology. 

Eric McGee, senior network engineer at TRG Datacenters, a data center vendor, explained why IBN is helpful to network administrators who want to better understand and manage their networks.

“One important networking technology trend that network engineers need to take note of is the emergence of intent-based networking,” McGee said. “The main role of IBN is to capture business intent and apply these insights across the network, ensuring that network administration is aligned with business intent. In other words, the IBN framework will receive an intent from the business and translate it, or encode it into the configuration of the network, resulting in the desired changes. Now, the network infrastructure is aligned with the business’s current needs.

“IBN also enables the automation of network administrative tasks involved, such as the configuration of networks, mitigation of risks, as well as the reporting and solving of network issues. Implementing IBN as a form of network administration makes the process of creating, managing, implementing, and monitoring network policies easier, simpler, and less labor-intensive. A lot of the manual effort put into traditional configuration management is made redundant when IBN is implemented.”

4. Holistic Networking Offerings

Traditional networking solutions typically need a variety of hardware and software components to work properly. 

However, as networks continue to evolve their software-defined, cloud, edge, and solutions, many networking vendors are offering more holistic networking packages to manage every aspect of the network.

Patrick MeLampy, Juniper Fellow at Juniper Networks, a top global networking company, believes that enterprise client-to-cloud connectivity is one of the biggest drivers behind more unified networking packages.

“I’d have to say that there are a few key networking trends that are gaining steam,” MeLampy said. “Enterprise client-to-cloud connectivity service offerings will take off. This means we’ll see Wi-Fi, wired, routing, and security capabilities pulled together, all in one simple offering, making it more efficient and effective for teams to manage ever-expanding networks.”

For more on cloud networking: The Cloud Networking Market

5. Managing Network Data With Different Ops Methodologies

With more software- and cloud-based networking solutions used across the board, several companies are looking into new ways to manage and read their networking data.

Richard Larkin, manager of North America sales engineering at NetBrain, a next-gen network operations company, believes that the knowledge and approach of different ops teams are particularly applicable to new ways of automating network data management. 

“The days of managing networks with SNMP polling and traps as well as Syslog data are almost over,” Larkin said. “Many enterprises still leverage these telemetry sources, but it’s not enough. We need a more comprehensive solution harvesting data, from API, CLI, packet, netflow, and other sources, to get the complete picture as well as visibility into SD-WAN, SDN, cloud, and SaaS offerings.

“A trend that I am seeing is the blending and blurring of lines between NetOps, SecOps, and DevOps. With networks becoming more software-defined and cloud-based, organizations are trying to fill the gap of the traditional network monitoring data (SNMP, Syslog, etc.) with homegrown solutions using Python, Ansible, and other coding. What would be interesting is if there was an easier way to codify the knowledge of the NetOps teams that required minimal coding and can be produced in minutes, not hours, days, and weeks.”

For more on networking management: The Network Management Market

The Future Of Cloud Networking

With the vitality in cloud networking for businesses, these trends above will further develop in the future, offering more opportunities for the growing market. From automation and network efficiency, businesses will see more benefits than ever.

Looking ahead, the future developments in cloud networking may include:

• Networking automation: Using network automation will help a company with a variety of tasks, including configuring, provisioning, managing, and testing network devices.
• Network-as-a-Service (NaaS): NaaS is a cloud model that allows users to control their network and attain the performance they expect from it without having to own, build, or maintain their infrastructure.
• 5G Cellular: 5G, the latest cellular update, allows a new network designed to connect virtually, including machines, devices, and more.
• Wi-Fi 6: Wi-Fi 6 is the new release for Wi-Fi network protocol that can be faster than its predecessors due to more focus on traffic and other technologies.
• Network Efficiency: With improved network scalability in the next couple of years, traffic will be aggregated for IP and Ethernet platforms. 
• Universal Networks: In the future, networking will have the ability to add new protocols and functions for better service. This can include services such as Ethernet services, mobile services, and more.

Along with the listed predictions and processes, more technologies are developing in networking, including AI, ML, the cloud, edge computing, Internet of Things (IoT), and more as they continue to play an increasingly important role in the future of networking. 

Bottom Line: Top Cloud Networking Trends

With remote training becoming a necessity in businesses, networking can help manage workers at home with a network strategy and remote AI support – a trend that leverages cloud networking to a great extent. 

Companies can use tools such as software-defined networking (SDN), intent-based networking, business intelligence (BI), and configuration management through their networking infrastructure.

Networking used to be based on hardware-defined networking, increasingly also offers services such as software-defined, cloud, edge, and networking solutions. 

For more information: Top 10 Enterprise Networking Companies