Historically, organizations were often lax about data classification, creating problems that compounded quickly and led to data sprawl, lost productivity, and security concerns. But as data becomes increasingly essential for business—and accumulates in massive volumes—organizations have begun to consider data classification a pillar of their data management efforts. Here are the six top data classification trends for 2023.

1. AI is Driving Data Classification Efforts

Artificial intelligence (AI) had a banner year in 2023, and data science—like most industries—has begun to reap the benefits. Legacy data classification systems required challenging implementations and lacked the ability to perform context-based classification, but new solutions use AI to incorporate content awareness and context analysis into classifying and sorting data.

AI powered automation in data classification can help companies analyze and label unstructured data at unprecedented scales, and with minimal human intervention. This allows organizations to classify more data more quickly. It also lets them circumvent the industry-wide qualified staffing shortage.

AI also provides data leaders with actionable visibility into how data is used, shared, and acted on by different users, making it easy to flag suspicious data.

2. More Data Regulations are Being Implemented and Enforced

As more and more data breaches come to light, especially in critical infrastructure, governments have begun to tighten their grip around tech companies that violate data management and localization principles. New data privacy laws abandon the harm-based approach—preventing and punishing violations of consumer data—in favor of a rights-based approach that gives individuals control of how their data is managed, used, and processed.

The European Union is currently undertaking its largest cross-border investigation under the General Data Protection Regulation (GDPR) and taking action against member states that allow data attacks to thrive. While the U.S. has historically had a more lenient approach toward how organizations collect and classify data, that might be changing—after passage of the watershed California Consumer Privacy Act (CCPA), other states including Colorado, Utah, and Virginia have pursued similar legislation.

Additional policies like the National Cybersecurity Strategy, Gramm-Leach-Bliley Act (GLBA), and Family Educational Rights and Privacy Act (FERPA) will create multiple federal regulators in the U.S. to oversee implementation of data governance policies, and assist with classification, usage, and archival of data in the entire data lifecycle management.

3. Better Technologies are Making Data Classification More Effective

Technology is fueling a new wave of data democratization, providing simpler access controls, more secure delivery, and greater decentralization. At the forefront is the integration of data fabric—which stitches together metadata to aid data classification—and data mesh, which can reduce information silos and aid in governance by putting the onus on teams that produce data.

The combination of technologies helps companies process data from multiple sources, producing faster insights and creating a frictionless web for all stakeholders to engage with processed data. It also helps build an autonomous, company-wide data classification and coverage interface that provides self-service access to fragmented datasets.

Enterprises can reduce operational expenses by up to 400 percent by classifying data without having to move it and creating a data abstraction layer. Enterprises can also manage their security postures with improved data access and intelligent query escalation, allowing them to build a top-down data service.

4. Zero-Trust Data Privacy Vaults are Being Used for Sensitive Data

Data classification plans must also secure confidential and restricted data by de-identifying critical datasets and exposing only the information needed to complete a task. As tech firms face greater compliance demands from regulators, privacy vaults are increasingly drawing attention as an interesting solution. A zero-trust vault eases personally identifiable information (PII) compliance concerns by providing a controlled environment to protect sensitive data.

Most privacy vaults use polymorphic encryption, two-factor authentication, and regular data audits to detect vulnerabilities and keep customer data attack-proof. They also allow governments and businesses to work together on privacy by design in big tech by redacting confidential datasets, tokenizing sensitive information, and restricting the flow of personal data in large language models (LLM) like ChatGPT.

Privacy vaults are especially popular in the pharmaceutical field, where proprietary research has to be protected across the drug lifecycle.

5. Unstructured Data is Powering Business Intelligence

Unstructured data—emails, text messages, and multimedia, for example—poses particular challenges for data classification. It is like the anti-matter of the universe in that it is difficult to detect and mostly impossible to analyze, but it accounts for a significant portion of the data enterprises collect and use.

The growing focus on unstructured data is driven by the time crunch that businesses face in a fiercely competitive market. They have to feed data pipelines faster, move only the data they need—and that has already been classified—and eliminate manual efforts to find classified datasets.

Finding ways to process and classify unstructured data can provide improved storage capacity, a data-driven way to measure consumer experience, and a better understanding of user sentiment.

Read our Comprehensive Guide to Data Pipeline Design.

6. Companies are Assessing Risks to Prevent Shadow Access

Shadow access—unintended, uninvited, and unnoticed access to datasets—is an increasingly exploited risk facing businesses with large volumes of poorly classified data. That risk is only expected to grow as more data gets stored and shared in the cloud.

About 80 percent of all data breaches occur because of existing credentials—employees intentionally or inadvertently share confidential information or access unauthorized applications and cloud services. With blurred lines between personal and professional domains and the growing complexity of cloud identity, shadow access has become an even thornier issue.

Because you can’t protect what you don’t know, new tools to assess risk for shadow access are garnering attention from data leaders. They allow them to identify data types that are vulnerable to security risks and take necessary steps to mitigate those risks.

Bottom Line: Enterprise Data Classification is Evolving

As enterprises race toward the creation of data-safe environments, their data classification policies will increasingly become one of the differentiating factors. At the moment, the field of data classification is in flux, driven by the advent of generative AI, a greater demand for customer experience, and growing pains of data sprawl. But organizations that tap into these innovations to shore up their data classification efforts and their larger data management strategies will ride the wave to a more successful, more secure, and more actionable data future.

Read The Future of Data Management to see other trends in how enterprises work with and keep tabs on mission critical information.

Experts predict 175 zettabytes of data worldwide within two years, much of it coming from IoT (Internet of Things) devices. Companies of all sizes should expect significant troves of data, most of it unstructured and not necessarily compatible with system of record (SOR) databases that have long driven mission-critical enterprise systems like enterprise resource planning (ERP).

Even unstructured data should be subject to many of the same rules that govern structured SOR data. For example, unstructured data must be secured with the highest levels of data integrity and reliability if the business is to depend on it. It must also meet regulatory and internal governance standards, and it must be able to move freely among systems and applications on clouds, internal data repositories, and mobile storage.

To keep pace with the enormous demands of managing voluminous high velocity and variegated data day-in and day-out, software-based tools and automation must be incorporated into data management practices. Newer automation technologies like data observability will only grow in importance, especially as user citizen development and localized data use expand.

All of these forces require careful consideration as enterprise IT builds its data management roadmap. Accordingly, here are seven emergent data management trends in 2023.

Hybrid End-to-End Data Management Frameworks

Enterprises can expect huge amounts of structured and unstructured data coming in from a wide range of sources, including outside cloud providers; IoT devices, robots, drones, RF readers, and MRI or CNC machines; internal SOR systems; and remote users working on smart phones and notepads. All of this data might be committed to long- or short- term storage in the on-premise data center, in a cloud, or on a mobile or distributed server platform. In some cases, real-time data may need to be monitored and/or accessed as it streams in real time.

In this hybrid environment, the data, its uses, and its users are diverse—data managers will need data management and security software that can span all of these hybrid activities and uses so data can be safely and securely transported and stored point to point.

IBM is a leader in the data management framework space, but SAP, Tibco, Talend, Oracle, and others also offer end-to end data fabric management solutions. A second aspect of data management is being able to secure data, no matter where it is sent from or where it resides—end-to-end security mesh software from vendors such as Fortinet, Palo Alto Networks, and Crowdstrike can meet this need.

The Consolidation of Data Observability Tools

Because many applications now use multiple cloud and on-premises platforms to access and process data, observability—the ability to track data and events across multiple platform and system barriers with software—is a key focus for enterprises looking to monitor end-to-end movements of data and applications. The issue with most organizations that are using observability tools today is that they are using too many different tools to effect end-to-end data and application visibility across platforms.

Vendors like Middleware and Datadog recognize this and are focused on delivering integrated, “single pane of glass” observability tool sets. These tools enable enterprises to reduce the number of different observability tools they use into a single toolset that’s able to monitor data and event movements across multiple cloud and on premises systems and platforms.

Master Data Management for Legacy Systems

As businesses move forward with new technologies, they face the challenge of figuring out what to do with older ones. But some of those continue to provide value as legacy systems—systems that are outdated or that continue to run mission-critical functions vital to the enterprise.

Some of these legacy systems—for example, enterprise resource planning (ERP) systems like SAP or Oracle—offer comprehensive, integrated master data management (MDM) toolsets for managing data on their cloud or on-premises solutions. Increasingly enterprises using these systems are adopting and deploying these MDM toolsets as part of their overall data governance strategies.

MDM tools offer user-friendly ways to manage system data and to import data from outside sources. MDM software provides a single view of the data, no matter where it resides, and IT sets the MDM business rules for data consistency, quality, security, and governance.

Data Management Using AI/ML

While the trend of using artificial intelligence and machine learning (AI/ML) for data management is not new, it continues to grow in popularity driven by big data concerns as the unprecedented volume of data enterprises are faced with managing collides with an ongoing staffing shortage across the tech industry as a whole—especially in data-focused roles.

AI and ML introduce highly valuable automation to manual processes that have been prone to human error. Foundational data management tasks like data identification and classification can be handled more efficiently and accurately by advanced technologies in the AI/ML space, and enterprises are using it to support more advanced data management tasks such as:

• Data cataloging
• Metadata management
• Data mapping
• Anomaly detection
• Metadata auto-discovery
• Data governance control monitoring

As AI/ML continues to evolve, we can expect to see software solutions that offer intelligent, learning-based approaches including search, discovery, and capacity planning.

Prioritizing Data Security

In the first quarter of 2023, over six million data records were breached worldwide. A data breach can destroy a company’s reputation, impact revenue, endanger customer loyalty, and get people fired.This is why security of all IT—especially as more IT moves to the edge and the IoT—is an important priority for CIOs and a major IT investment area.

To meet data security challenges, security solution providers are moving toward more end-to-end security fabric solutions. They are offering training for employees and IT, since increases in user citizen development and poor user security habits can be major causes of breaches.

Although many of these security functions will be performed by the IT and network groups, clean, secure, and reliable data is foremost a database administrator, data analyst, and data storage concern as well.

Automating Data Preparation

The exponential growth of big data volumes and a shrinking pool of data science talent is stressing organizations. In some cases, more than 60 percent of expensive data science time is spent cleaning and preparing data.

Software vendors want to change this corporate pain point with an increase in data preparation and cleaning automation software that can perform these tedious, manual operations. Automated data preparation solutions ingest, store, organize, and maintain data, often using AI and ML, and can handle such manually intensive tasks as data preparation and data cleansing.

Using Blockchain and Distributed Ledger Technology

Distributed ledger systems enable enterprises to maintain more secure transaction records, track assets, and keep audit trails. This technology, along with blockchain technology, stores data in a decentralized form that cannot be altered, improving the authenticity and accuracy of records related to data handling. This includes financial transaction data, sensitive data retrieval activity, and more.

Blockchain technology can be used in data management to improve the security, shareability, and consistency of data. It can also be used to provide automatic verification, offering avenues to improve data governance and security.

Bottom Line: The Future of Data Management

As businesses confront the need to collect and analyze massive volumes of data from a variety of sources, they seek new means of data management that can keep pace with the expanding need. Cutting edge technologies like AI/ML and blockchain can be used to automate and enhance some aspects of data management, and software vendors are incorporating them into their platforms to make them an integral part of the work. As new technologies continue to evolve, data management methods will evolve with them, integrating them into processes driven by increasing demand.

Read next: Structured Data: Examples, Sources, and How it Works

This article explores the benefits and transformative potential of digital transformation across various industries.

What is Digital Transformation?

Digital transformation will look different for every company. It’s part technology initiative and part culture change, with a heavy dose of workflow re-imagining thrown in.

For example, if a company started with digitization—the term for transferring paper and analog data to a digital format without making any changes to business processes—it might then realize that the convenience of their new format could be matched with new ways of doing business. That moment in a digital transition is when digital transformation happens.

Here’s a good way to think about it: digital transformation is creating fundamental changes in how a business operates and the value it provides customers by introducing technology into all areas of its work.

Thinking beyond going paperless, digital transformation could mean automating processes to create efficiencies and improve accuracy, or integrating all new customer relationship management and finance and accounting systems across an organization. Digital transformation is a broad term encompassing many aspects of how businesses implement technologies and the processes around them.

The goal is not the technology itself, but the improvements it can bring to how the work is done and the value it brings to the organization and its customers—an important distinction.

Learn more: 5 Digital Transformation Examples

Enterprise Digital Transformation Through AI

Larger enterprises have engaged with digital transformation practices for years, watching the latest technology trends and brainstorming how new developments could advance their business model. One transformative advancement for both industry and consumers has come in the form of streaming or multimedia that users can access at any time via the internet. Major companies in the television, film, gaming, and music industries are some of the biggest trailblazers in the digital transformation world.

Spotify is an example of constant digital transformation. The company’s goal is to create the most personalized user experience (UX) possible for listeners, and it has consistently done that through data analytics, artificial intelligence (AI), and machine learning.

Here are just a couple examples of how the company has used new technologies to tailor customer experiences (CX):

Made For You Playlists

Based on a user’s behavioral trends and previous listens, Spotify creates “made for you” playlists to match the different artists, genres, and tempos that it believes they will like most. It does this through a process called collaborative filtering, Spotify compares both qualitative and quantitative data from different users with similar listening patterns and makes recommendations to each based on the habits of those similar listeners.

Release Radar

This Spotify feature alerts users to new music from artists they already love or artists Spotify thinks they will love. Once again, Spotify uses collaborative filtering, but also natural language processing to find out what you like and listen in on the online chatter about recent releases. If a new album is considered high quality and matches a certain genre, it may end up in your release queue. This is also great exposure for new artists who match the tastes of Spotify listeners.

Streaming is a prime example of how digital transformation happens at the enterprise level, and it is one of the clearest to the millions of users who frequently engage with streaming technologies.

Digital Transformation In Customer Service And Engagement

Companies of varying sizes and industries have adjusted their customer service approach to meet customers virtually and in real-time. With a growing number of available social media platforms, smart applications, and simple website development and management tools, many organizations are using these resources to digitally transform the way they talk to customers—here are a few examples.

Social Media

Social media has served as a primary tool for connecting with other people virtually, but it continues to expand into customer service and e-commerce. Some of the examples of digital transformation that most major companies have implemented on their social media channels include the following:

• Answering customer questions and handling complaints in the comments of social media posts
• Posting challenges, events, and discounts for customers
• Selling products through native e-commerce features on Instagram and Facebook
• Finding other fun ways to start conversations with customers and other companies.

Chatbots

Chatbots are common website add-ons that companies use to digitally transform customer service. Bypassing traditional contact center models, chatbots help customers at any time of day with a pre-programmed bot that answers their questions or helps them navigate the website. Chatbots also allow customers to self-segment their personal data for your company’s database, making their experience more personalized and giving you more insight into your customer base.

Self-Help Knowledge Bases

Self-help knowledge bases provide another way to bypass traditional contact center models. By creating an FAQ library with short articles and multimedia resources, both your customers and your employees can research their questions. This self-service option lessens the strain on customer service representatives. Several major customer relationship management (CRM) platforms, such as HubSpot and Salesforce, enable this feature through service hubs.

Learn more: How to Use a Knowledge Management System to Improve Customer Service

Digital Transformation in the COVID-19 Era

The COVID-19 pandemic forced a lot of digital transformation upon a lot of companies. The widespread lockdowns and stay-at-home orders drove new uses of tools and technologies for business to maintain customer relationships in the chaos. Here are a few ways we saw digital transformation save industries and institutions from total collapse during the pandemic:

Widespread Use Of Video Conferencing Platforms

Stay-at-home orders sent non-essential employees away from the office to work from home, which completely disrupted the traditional in-office meeting workflow. Video conferencing platforms already had a place in many businesses, but during the pandemic, they became a staple that transformed the way we meet with colleagues. You can share your screen to guide someone through a process, type questions into a chat while others are presenting, and even host quick video meetings for mental health checks with faraway teammates. The widespread adoption of this technology has changed the way we work, enabling the rise of remote work.

Virtual conferencing platforms also gained major traction, considering you can’t host industry speaking conferences if no one is allowed to travel. Many hosting organizations launched virtual event platforms to keep their events going during COVID-19, hosting live and pre-recorded speaker events where people could pay for digital access.

Past conferences involved extensive event planning, catering, hotels, and air-travel fees, but through this forced digital transformation, many organizations are discovering that you don’t need a physical venue to host an informational event.

E-Learning

The way students learn and teachers teach has changed dramatically during the pandemic. Some students are learning virtually, some are in person, and many are learning in a hybrid model. This shift in the learning experience required several points of digital transformation, such as:

• Using learning management systems (LMS) to assign and turn in homework and tests
• Launching video conferencing platforms for teacher lectures and student presentations
• Ensuring students have internet access and computers or tablets that can securely connect to the school’s network

Many students are heading back to in-person learning. However, due to the digital transformation school systems had to make during the pandemic, classrooms will likely incorporate more virtual learning elements into lesson plans, particularly for students who struggle with accessibility in a traditional classroom environment.

Virtual Dining Options

Restaurants were some of the businesses hit hardest by pandemic restrictions, but many of them pivoted and maintained a revenue stream through digital transformation. Restaurants expanded their carry-out and delivery options, partnering with food delivery applications and expanding their customer-facing order applications.

As in-person dining slowly returned, many restaurants found a new form of digital transformation necessary. In order to comply with health department standards and to stay open, they began the digitalization of their menus. This move requires customers to scan a QR code and view the menu on their personal device, instead of receiving a physical copy. As COVID restrictions are fully lifted, these digital transformations may decrease in popularity, but many are likely to stick around because of their convenience for both restaurant staff and customers.

Learn more: The Primary Reasons Digital Transformation Efforts Fail

Bottom Line: Digital Transformation

Digital transformation is a means for businesses to add value to the products and services they provide customers by changing not just the technology they use, but their processes and ways of thinking about how to use that technology. It’s less about implementation than it is about effecting cultural change within the company. Enterprises interested in exploring new avenues of digital transformation can engage with consulting firms to help identify opportunities and redefine their processes, or they can start on a smaller scale with internal efforts. The only wrong way is to not explore digital transformation at all—the future is digital, and companies that fail to embrace it risk falling behind.

Read next: Top 7 Digital Transformation Companies

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

Meanwhile, the ever-growing value of big data is driving data scientists to increase their access along with their ability to mine and analyze data for insights and information by adapting how data repositories are managed in relation to the type of data they house. While some legacy and on-premises solutions continue to be indispensable, a mass shift to the cloud is proving to be the answer to many of the problems organizations are facing in regards to data volume, compatibility, and accessibility.

Companies of various sizes and industries adapt to progress at different rates and may migrate data for different reasons. The five major trends in data migration in 2023 reflect the industry’s attitude as a whole toward solving specific problems.

1. A Shift Towards Data Lakehouses

Data lakehouses are open data management architectures that combine the flexibility, cost-efficiency, and scale of data lakes with the data management abilities of data warehouses. The result is a unified platform used for the storage, processing, and analysis of both structured and unstructured data. One reason this approach is gaining popularity is a sustained desire to break down data silos, improve quality, and accelerate data-driven decision-making within organizations.

Data lakehouses’ large capacity enables them to handle large volumes of data in real time, making them ideal for live consumer data, Internet of Things (IoT) networks, and physical sensors. Their ability to process data from multiple sources makes it easier for organizations to gain insights from multiple data streams.

Additionally, the centralization of data lakehouses allows for a unified, up-to-date view of data across an entire organization, facilitating inter-departmental collaboration on data-based projects and greatly reducing the costs and complexity of hosting multiple data storage and processing solutions.

2. A Focus on AI and Automation in Governance

Data migration helps organizations keep pace by ensuring their systems are able to accommodate the ever-increasing flow of new data. To simplify the already complex and time-consuming task of data governance, many companies are turning to artificial intelligence (AI)/machine learning (ML) algorithms and automation.

These technologies have revolutionized data migration by allowing organizations and data managers to automate some of the many manual processes it involves. It also enables them to reduce the risk of failures due to human error and execute the migration process more accurately and efficiently. With the help of smart algorithms, organizations can also better gain insights into their data than previously possible while identifying and eliminating data duplicates, which may reduce storage costs and improve performance.

Thanks to the recent boom in AI and ML-based technologies being developed and partially launched by a number of cloud computing giants, including Microsoft and Google, the role of such technologies in the more critical processes of data migration is likely to increase as the models become more and more sophisticated.

3. Expanding Storage Capacity

The world is expected to generate around 120 zettabytes of data in 2023, a nearly 24 percent increase from the prior year. This data is generated from a wide variety of sources, including IoT devices, log files, and marketing research. In this case, bigger is better—many organizations are looking to embrace big data by expanding storage capacities through novel methods of data storage.

One prominent option is cloud storage, which stands out as a scalable, reliable solution that’s also easily accessible over the internet. However, one of the challenges that arises with data migration to the cloud is maintaining security during transit. Organizations must carefully plan their migration strategies—including encryption, backup, and recovery plans—to protect financial and medical data and personal information while it is at risk.

Organizations can also benefit from an increase in agility and compounded value of structured and unstructured data by expanding their overall data storage capacity through flexible and scalable means.

4. Handling Unstructured Data

Most data sources produce semi-structured or unstructured data that cannot be easily organized and categorized. Company mergers and system updates are prominent sources of unstructured data—the initial categorization and structure of the data must be shed in order to fit into a different system. Unstructured data tends to be much larger in volume than structured data carrying the same amount of information and insights.

This poses a problem when migrating data. Not only is the massive volume costly to transfer and secure, both in-transit and at-rest, but it cannot be analyzed or stored in relational databases. However, that doesn’t make it void of value, as many organizations are seeking data science and migration solutions that would help structure incoming data.

Solving the unstructured data problem is a time-sensitive endeavor for many organizations. That’s because situational data quickly loses its value with time and gets replaced by more recent data, often in greater volume.

5. A Move From On-Premises Legacy Systems to Cloud Storage

Most data originates in the cloud, from such sources as digital logs, monitoring devices, customer transactions, and IoT devices and sensors. Many organizations are finding it more efficient to migrate entirely to the cloud rather than remaining split between legacy on-premises systems and cloud storage.

This approach would involve the integration of legacy data and systems with already-present data stored in the cloud, creating a more unified and comprehensive approach to data management and enabling remote access. A move to the cloud would also be accompanied by embracing multi-cloud architectures, allowing companies to optimize costs by working and switching between multiple cloud providers simultaneously.

Moving entirely to the cloud would also facilitate data storage segmentation, enabling data managers to differentiate data by type, purpose, and origin in addition to sensitivity and the level of security it may require. Organizations with data split between legacy and cloud systems may seek to unify the multiple sources in the cloud, enabling them to develop a richer, more holistic view of their data and how they might be able to use it.

Predictions for the Future of Data Migration

Data migration is expected to continue to grow in popularity alongside the exponential growth in the average volume of data produced annually by organizations. As businesses increasingly adopt cloud-based alternatives to everything from computing and processing to hosting software, cloud-based data solutions are likely to follow.

This will spark a wave of innovation, creating modern tools and technologies that aim to simplify the data migration process, ensuring the security and reliability of data in transit. Combined with the latest advancements in AI, ML, and automation, the migration process is likely to become faster, more efficient, and less prone to errors, making data migration as a concept more accessible to startups and emerging businesses who want to shift to the cloud and make the most out of their 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.

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.

With the Internet of Things (IoT) and the integration of advanced technologies like Artificial Intelligence (AI) and Machine Learning (ML), there is a remarkable opportunity for enterprises to harness real-time data and extract valuable insights.

Even among such transformative technologies, Digital Twin stands out.

Digital Twin enables businesses to embrace automation and virtualization, revolutionizing industries across the board. From manufacturing and healthcare to telecom, automotive and aerospace, the applications of Digital Twin solutions are far-reaching.

By seamlessly replicating physical assets, processes, and systems into virtual models, digital twins empower enterprises to optimize production processes, streamline product design, exercise precise process control, monitor risks and drive superior performance management.

Unsurprisingly, the global Digital Twin market, estimated at USD 11.12 billion in 2022, continues to expand rapidly.

In this comprehensive guide, we explore the concept of digital twins and compare some of the leading Digital Twin solutions available in the market today.

What is a Digital Twin?

Any object or environment can be virtually represented using its Digital Twin. It is a virtual model that can accurately replicate a physical system.

A Digital Twin is essentially a rich virtual environment that facilitates bi-directional information flow with great potential to improve products and processes.

For instance, a Digital Twin can be used for simulations, testing and monitoring without making any changes to its physical counterpart. As a result, instead of the conventional and time-consuming physical testing approach, it is possible to improve real-world systems rapidly and at a fraction of the cost.

Historical Background

In 1991, David Geelrnter first voiced the idea of Digital Twins in his book “Mirror Worlds,” and Dr. Michael Grieves applied the concept in 2002 when he proposed the idea at a conference under the name “Product Lifecycle Management.”

The term “digital twin” also appeared in the draft version of NASA’s 2010 Roadmap Report, but the research organization was using the idea as far back as the 1960s when it created complex simulations of spacecraft for its space exploration missions.

Benefits of Digital Twin Solutions

Digital Twin technology has made sizable progress in the last few years, introducing next-generation digital transformation opportunities for businesses. Some of the key benefits of digital twin solutions include:

Improved efficiency
Digital Twin solutions can improve operational efficiency with strategically planned production processes. They can identify process failures and associated risks and speed up the development lifecycle, thus increasing efficiency, productivity and overall performance.

Real-time monitoring
Digital twins facilitate remote monitoring and control of the system’s performance. With real-time data, all the central aspects of the production and design processes can be validated to make the right decisions at the right time.

Better decision-making
Effective research and design offer the needed product refinements and better insights with abundant data regarding performance outcomes. Thus, Digital Twin solutions can help businesses with better-informed decisions.

Applications

Digital Twin solutions are already being implemented in major applications. Some of these include the following:

Manufacturing and industrial processes
Digital Twins can simulate and optimize manufacturing processes, monitor equipment performance and improve overall operational efficiency. They enable real-time monitoring, predictive maintenance and virtual testing of different scenarios.

Smart cities
These digital models are significantly valuable for creating virtual replicas of cities that enable urban planners to model and optimize infrastructure, transportation systems, energy consumption and other aspects of urban development.

Construction and building management
The construction industry can leverage Digital Twin technology to simulate and optimize building designs, construction processes and ongoing facility management. These models help owners and facility managers identify potential issues, optimize energy usage and improve building maintenance.

Retail and supply chain
With Digital Twins, it is possible to gain real-time visibility into the supply chain, which helps predict demand more accurately, optimize inventory levels and improve overall logistics efficiency. These models also enable retailers to create personalized shopping experiences and optimize store layouts based on insights generated through customer data.

Top Digital Twin Solutions

Some of the top Digital Twin solutions include the following:

Azure Digital Twins

Microsoft’s Azure Digital Twins helps create digital models of the physical environment using IoT spatial intelligence.

Overview
Azure Digital Twins is a Platform-as-a-Service (PaaS) offering enterprise-grade IoT-connected solutions. It helps businesses create comprehensive digital models for places, business processes and real-world systems.

Features

• Custom domain models using Digital Twins Definition Language
• Live execution environment representation using live graphs
• Integration with Azure IoT Hubs and LogicApps, REST APIs for system input
• Actionable insights using Azure Data Analytics
• High-level security and scalability
• Simple and predictable pricing

Applications

• Creating data-driven workspaces
• Optimizing business costs and operations
• Improved product development process
• Model cities, factories, firms, buildings and similar environments

Pricing

A free account in Azure offers a $200 credit for 30 days. Azure has customized pricing plans. Check the pricing page for more details.

Ansys Twin Builder

Ansys designs multiphysics software solutions for business innovation. Ansys Twin Builder helps businesses in creating and deploying Digital Twin models.

Overview
This powerful digital platform helps develop simulation-based Digital Twin models. It is an open solution that uses Hybrid Analytics for integrated multi-domain system simulation. It can efficiently model real-world systems, mirroring their life and experience.

Features 

• Increased Digital Twin Prediction Accuracy
• Faster simulation using sophisticated solver synchronization
• Integrated with high-performance compute resources and extensive model libraries
• Reduced-Order-Model (ROM) interfaces for detailed simulations

Applications

• Industrial asset optimization and management
• Battery management systems
• Vehicle Powertrain Simulation
• Improving interoperability and simulation stability

Pricing
Ansys Twin Builder has a free trial option for 30 days. Request a trial here and contact their experts for pricing plans based on requirements.

Eclipse Ditto

Eclipse Foundation offers a global platform for open innovation and collaboration. This unique model has an open-source framework called Ditto for IoT and Digital Twin solutions.

Overview
Eclipse Ditto helps businesses build digital twins of assets with internet connectivity. It is an IoT middleware and can be merged into existing backend systems with supported protocols.

Features 

• Offers web APIs for simplified workload
• Microservices with the data store
• Static metadata management
• JavaScript Object Notation (JSON) based text protocol for communication

Applications

• Device-as-a-Service for synchronizing digital twin with the physical system
• State management for digital twins
• Access control enforcement with authorized API calls

Pricing
Eclipse is a free, open-source platform dedicated to development services. Contact the company through multiple channels here.

Aveva

The British multinational company AVEVA offers cutting-edge industrial software solutions. It helps businesses build digital twins for driving asset excellence with minimized risks.

Overview
AVEVA designs smart software solutions for leading industrial businesses. Its Digital Twin software solution spans the complete lifecycle of the asset. It is a cloud-based, open, vendor-agnostic platform that covers both engineering and IT operations.

Features 

• Whole-model visualization with touch-controls
• True digital thread with engineering and real-time data integration
• Wide range of engineering, structural and analytics models
• Historical and real-data collections with AVEVA PI System
• Integrated with high-end AVEVA software solutions for deeper contextualization

Applications

• Accelerated process design
• Reduced operational risks
• Production optimization
• Enterprise visualization

Pricing
AVEVA offers a flexible software subscription program with minimized upfront costs and fast Return on Investment (ROI). Learn more and talk to their experts to get the best plan here.

3DEXPERIENCE

The French multinational Dassault Systemes is famous for its creative and innovative sustainable software solutions. It has been listed in the Fortune 50 list by BCG. The company offers a 3D experience platform for virtual or Digital Twin solutions.

Overview
3D Experience is focused on converging the virtual and real worlds. This platform is an all-in-one solution with combined SaaS, PaaS, and IaaS offerings.

Features

• Easy-to-use interface for easy interaction
• Immediate access to enterprise-class technologies and apps like DELMIA, SIMULIA, CATIA and more
• Automatic updates with frequent new features
• Fully secured data encryption at all layers

Applications

• All-through production planning and lean operation
• Sustainable business initiatives
• Performance, reliability and safety assessment
• Improved business resilience with prior impact evaluation

Pricing
Find the entire portfolio of 3D Experience products here. Subscription plans are based on requirements.

Digital Twin Exchange

The leading technical giant IBM has been pioneering Digital Twin solutions for a long time, and offers an e-commerce platform called IBM Digital Twin Exchange that helps businesses buy and sell Digital Twin assets.

Overview
The Digital Twin Exchange platform by IBM is a rapidly growing partner ecosystem. It is a one-stop shop for Digital Twin solutions customers who can easily shop from a wide range of credible products based on requirements and budget.

Features

• IBM Support for any technical issues or assistance
• Faster integration with Enterprise Resource Planning (ERP) and Enterprise Asset Management (EAM) systems
• Increased level of safety
• Reduced risk of failure

Applications

• Smart operations
• Supply chain efficiency
• Designing predictive models
• Managing enterprise-wise digital assets

Pricing
The platform features a wide range of products—find the list and prices here.

Oracle IoT Digital Twin Framework

Oracle Corporation offers Digital Twin solutions integrated with its IoT platform. The Oracle IoT Digital Twin Framework helps businesses with device virtualization and implementation.

Overview
Oracle IoT implements the digital twin concept comprehensively. It helps in designing the digital proxy of any real-world asset or system. Oracle also offers a Digital Twin Simulator for developing ready-to-use simulation models.

Features

• Configurable alerts for simulated devices
• JSON-based model for visual representation
• Integrated ML techniques for robust analytical model
• Product Lifecycle Management (PLM)  tools for industrial twins

Applications

• Better visibility with interconnected systems
• Well-designed interfaces for What-if analysis
• Connection with back-end applications for real-time configuration
• Simulation models development without hardware setup

Pricing
Oracle offers a uniform pricing structure with committed use discounts and other rewards. Check estimated prices using the Oracle Cost Estimator.

Amazon IOT TwinMaker

Amazon has been extending intelligent software solutions through its AWS platform, and offers Digital twin solutions with AWS IoT TwinMaker.

Overview
AWS IoT TwinMaker helps businesses develop operational digital twins. This platform offers the tools to efficiently create a virtual representation of existing physical systems with real-world data integration for faster monitoring operations.

Features

• Built-in connectors for richer data access
• Advanced digital twin graphs for defined relationships
• Interactive 3D view with scenes, workspace and resources
• Plug-ins for Grafana for customized visualization panels

Applications

• Optimization of industrial operations
• Increasing production output
• Improved equipment performance
• Low-code web application building

Pricing
AWS IoT TwinMaker can be used for free with the AWS Free Tier. After free usage expires, purchase a pricing plan based on usage requirements. Find pricing details here.

GE Digital

General Electric offers innovative technology solutions for different industry verticals. In addition, GE Digital offers Digital Twin solutions integrated with cutting-edge technologies and services.

Overview
GE Digital is a rich platform that specifically designs digital twins for industrial applications. Being a co-founder of the Digital Twin Consortium, GE is focused on industrial optimization and currently has more than 330 Digital Twin blueprints.

Features

• Cost-effective design and maintenance solutions
• Reduced planning time
• Productivity improvements
• Advanced analytics with immersive visualization

Applications

• Network Digital Twin solutions for grid operations
• Performance Intelligence with greater speed and efficiency
• Process Digital Twin solutions
• Smarter manufacturing with AI and Analytics

Pricing
Request a free trial version and demo here.

How to Choose Digital Twin Solutions

Implementing Digital Twin solutions can be challenging. It requires an in-depth evaluation of the current systems and efficient strategic planning. Here are some tips to consider when evaluating different Digital Twin solutions.

Selecting the right model
Businesses need to exclusively analyze their requirements from the Digital twin solutions. If there are specific use cases or just enhanced feature requirements, opt for platforms capable of addressing these requirements.

Also, choose the right model that can cater to your business vision and generate the required value. The primary digital twin types are Physics-based Twins and Data-based Twins. Physics-based digital twins are built from CAD files and work best for simple objects. It is best suitable when immediate decisions are not necessary.

Data-based twins rely on Machine Learning algorithms that can produce more accurate and quicker results. Thus, they work best for complex products and processes.

There are also hybrid digital twins that combine both approaches and are more efficient. Therefore, it is crucial to explicitly define the challenges that you want to address and then finalize the model that will work best for you.

Agile implementation
Maturity tests can evaluate the business’s current digital product development capabilities. It addresses the system complexities and helps prioritize the investment areas to implement digital twin technology effectively.

The initial months must be invested in developing an MVP (Minimum Viable Product) with a cross-functional, agile team. It can maximize value gains from the beginning. Based on the learnings, the implementation plan can be calibrated.

Ready-to-use solutions
As industry leaders already offer ready-to-use solutions, businesses need not invest a hefty amount in developing the necessary infrastructure and capabilities for incorporating Digital Twin technology. Instead, they can save considerable time, effort and resources by exploring these vendors and facilitating the development process.

It is vital to purchase Digital Twin tools, elements and blueprints from a single vendor to avoid compatibility and integration challenges.

Bottom Line: Top Digital Twin Solutions

Digital twins combine real and digital words and seamlessly integrate the entire value chain to create the best-in-class products. They optimize both the product and the production.

More and more tech leaders are entering the arena to develop efficient Digital Twin solutions and foster new approaches to help businesses operate faster and smarter. The steady growth in the global Digital Twin market proves that more enterprises are willing to leverage these solutions.

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