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Data and Analytics Trends 2023

Elevate data value and capabilities to improve business outcomes.

Data is a unique resource that keeps growing, presenting opportunities along the way. CIOs and IT leaders can use rapidly evolving technologies and capabilities to harness this data and its value for the organization.

IT leaders must prepare their teams and operations with the right knowledge, capabilities, and strategies to make sure they remain competitive in 2023 and beyond. Nine trends that expand on the three common Vs of data – volume, velocity, and variety – can help guide the way.

Focus on trends that align with your opportunities and challenges

The path to becoming more competitive in a data-driven economy differs from one company to the next. IT leaders should use the data and analytics trends that align most with their organizational goals and can lead to positive business outcomes.

  1. Prioritize your investments: Conduct market analysis and prioritize the data and analytics investments that will be critical to your business.
  2. Build a robust strategy: Identify a clear path between your data vision and business outcomes to build a strategy that’s a good fit for your organization.
  3. Inspire practical innovation: Follow a pragmatic approach to implementing trends that range from data gravity and democratization to data monetization and augmented analytics.

Data and Analytics Trends 2023 Research & Tools

1. Data and Analytics Trends Report 2023 – A report that explores nine data use cases for emerging technologies that can improve on capabilities needed to compete in the data-driven economy.

Data technologies are rapidly evolving. Understanding data's art of the possible is critical. However, to adapt to these upcoming data trends, a solid data management foundation is required. This report explores nine data trends based on the proven framework of data V's: Volume, Velocity, Variety, Veracity, Value, Virtue, Visualization, Virality, and Viscosity.

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Data and Analytics Trends Report 2023


Nine Data Trends for 2023

In this report, we explore nine data use cases for emerging technologies that can improve on capabilities needed to compete in the data-driven economy. Use cases combine emerging data trends and modernization of existing capabilities.

    • Data Gravity
    • Democratizing Real-Time Data
    • Augmented Data Management
    • Identity Authenticity
  5. VALUE
    • Data Monetization
    • Adaptive Data Governance
    • AI-Driven Storytelling & Augmented Analytics
    • Data Marketplace
    • DevOps – DataOps – XOps


Data Gravity

Trend 01 Demand for storage and bandwidth continues to grow

When organizations begin to prioritize data, they first consider the sheer volume of data, which will influence data system design. Your data systems must consider the existing and growing volume of data by assessing industry initiatives such as digital transformation, Industry 4.0, IoT, consumer digital footprint, etc.

The largest data center in the world is a citadel in Reno, Nevada, that stretches over 7.2 million square feet!

Source: Cloudwards, 2022

IoT devices will generate 79.4 zettabytes of data
by 2025.

Source: IDC, 2019

There were about 97
zettabytes of data generated worldwide in 2022.

Source: “Volume of Data,” Statista, 2022


Data Gravity

Data attracts more data and an ecosystem of applications and services

SharePoint, OneDrive, Google Drive, and Dropbox offer APIs and integration opportunities for developers to enhance their products.

Social media platforms thought about this early by allowing for an ecosystem of filters, apps, games, and effects that engage their users with little to no additional effort from internal resources.

The image contains four logos. SharePoint, OneDrive, Google Drive, and Dropbox.


Data Gravity

Focus on data gravity and avoid cloud repatriation

Data gravity is the tendency of data to attract applications, services, and other data. A growing number of cloud migration decisions will be made based on the data gravity concept. It will become increasingly important in data strategies, with failure potentially resulting in costly cloud repatriations.

Emerging technologies and capabilities:

Data Lakehouse, Data Mesh, Data Fabric, Hybrid Data, Cloud Data, Edge Computing


Centralized cloud storage going down in 2 years


Hybrid storage (centralized + edge) going up in 2 years


Source: CIO, 2022


Data Gravity

What worked for terabytes is ineffective for petabytes

When compared to on-premises infrastructure, cloud computing is less expensive and easier to implement. However, poor data replication and data gravity can significantly increase cloud costs to the point of failure. Data gravity will help organizations make better cloud migration decisions.

It is also critical to recognize changes in the industry landscape. The goal of data processing and analytics is to generate the right data for users to act on. In most cases, the user is a human being, but in the case of autonomous driving (AD), the car takes on the role of the user (DXC Technology).

To avoid cloud repatriation, it will become prudent for all organizations to consider data gravity and the timing of cloud migration.

The image contains a diagram on data gravity.


Democratizing Real-Time Data

Trend 02 Real-time analytics presents an important differentiator

The velocity element of data can be assessed from two standpoints: the speed at which data is being generated and how fast the organization needs to respond to the incoming information through capture, analysis, and use. Traditionally data was processed in a batch format (all at once or in incremental nightly data loads). There is a growing demand to process data continuously using streaming data-processing techniques.

Emerging technologies and capabilities:

Edge Computing

Google announced it has a quantum computer that is 100 million times faster than any classical computer in its lab.

Source: Science Alert, 2015

The number of qubits in quantum computers has been increasing dramatically, from 2 qubits in 1998 to 128 qubits in 2019.

Source: Statista, 2019

IBM released a 433-qubit quantum chip named Osprey in 2022 and expects to surpass 1,000 qubits with its next chip, Condor, in 2023.

Source: Nature, 2023


Democratizing Real-Time Data

Make data accessible to everyone in real time

  • 90% of an organization’s data is replicated or redundant.
  • Build API and web services that allow for live access to data.
  • Most social media platforms, like Twitter and Facebook, have APIs that offer access to incredible amounts of data and insights.


Democratizing Real-Time Data

Trend in Data Velocity

Data democratization means data is widely accessible to all stakeholders without bottlenecks or barriers. Success in data democratization comes with ubiquitous real-time analytics. Google highlights a need to address democratization in two different frames:

  1. Democratizing stream analytics for all businesses to ensure real-time data at the company level.
  2. Democratizing stream analytics for all personas and the ability of all users to generate real-time insights.

Emerging technologies and capabilities:

Data Lakehouse, Streaming API Ecosystem, Industry 4.0, Zero-Copy Cloning

Nearly 70% of all new vehicles globally will be connected to the internet by 2023.

Source: “Connected light-duty vehicles,” Statista, 2022


Democratizing Real-Time Data

Enable real-time processing with API

In the past, data democratization has largely translated into a free data set and open data portals. This has allowed the government to freely share data with the public. Also, the data science community has embraced the availability of large data sets such as weather data, stock data, etc. In the future, more focus will be on the combination of IoT and steaming analytics, which will provide better responsiveness and agility.

Many researchers, media companies, and organizations now have easy access to the Twitter/Facebook API platform to study various aspects of human behavior and sentiments. Large technology companies have already democratized their data using real-time APIs.

Thousands of sources for open data are available at your local municipalities alone.

6G will push Wi-Fi connectivity to 1 terabyte per second! This is expected to become commercially available by 2030.


Augmented Data Management

Trend 03 Need to manage unstructured data

The variety of data types is increasingly diverse. Structured data often comes from relational databases, while unstructured data comes from several sources such as photos, video, text documents, cell phones, etc. The variety of data is where technology can drive business value. However, unstructured data also poses a risk, especially for external data.

The number of IoT devices could rise to 30.9 billion by 2025.

Source: “IoT and Non-IoT Connections Worldwide,” Statista, 2022

The global edge computing market is expected to reach $250.6 billion by 2024.

Source: “Edge Computing,” Statista, 2022

Genomics research is expected to generate between 2 and 40 exabytes of data within the next decade.

Source: NIH, 2022


Augmented Data Management

Employ AI to automate data management

New tools will enhance many aspects of data management:

  • Data preparation, integration, cataloging, and quality
  • Metadata management
  • Master data management

Enabling AI-assisted decision-making tools

The image contains logos of the AI-assisted decision-making tools. Informatica, collibra, OCTOPAI.


Augmented Data Management

Trend in Data Variety

Augmented data management will enhance or automate data management capabilities by leveraging AI and related advanced techniques. It is quite possible to leverage existing data management tools and techniques, but most experts have recognized that more work and advanced patterns are needed to solve many complex data problems.

Emerging technologies and capabilities:

Data Factory, Data Mesh, Data Fabric, Artificial Intelligence, Machine Learning


Augmented Data Management

Data Fabric vs. Data Mesh: The Data Journey continues at an accelerated pace

Data Fabric

Data Mesh

Data fabric is an architecture that facilitates the end-to-end integration of various data pipelines and cloud environments using intelligent and automated systems. It’s a data integration pattern to unify disparate data systems, embed governance, strengthen security and privacy measures, and provide more data accessibility to workers and particularly to business users.

The data mesh architecture is an approach that aligns data sources by business domains, or functions, with data owners. With data ownership decentralization, data owners can create data products for their respective domains, meaning data consumers, both data scientists and business users, can use a combination of these data products for data analytics and data science.

More Unstructured Data

95% of businesses cite the need to manage unstructured data as a problem for their business.


Identity Authenticity

Trend 04 Veracity of data is a true test of your data capabilities

Data veracity is defined as the accuracy or truthfulness of a data set. More and more data is created in semi-structured and unstructured formats and originates from largely uncontrolled sources (e.g. social media platforms, external sources). The reliability and quality of the data being integrated should be a top concern. The veracity of data is imperative when looking to use data for predictive purposes. For example, energy companies rely heavily on weather patterns to optimize their service outputs, but weather patterns have an element of unpredictability.

Data quality affects overall labor productivity by as much as 20%, and 30% of operating expenses are due to insufficient data.

Source: Pragmatic Works, 2017

Bad data costs up to
15% to 25% of revenue.

Source: MIT Sloan Management Review, 2017


Identity Authenticity

Veracity of data is a true test of your data capabilities

  • Stop creating your own identity architectures and instead integrate a tried-and-true platform.
  • Aim for a single source of truth for digital identity.
  • Establish data governance that can withstand scrutiny.
  • Imagine a day in the future where verified accounts on social media platforms are available.
  • Zero-trust architecture should be used.


Identity Authenticity

Trend in Data Veracity

Veracity is a concept deeply linked to identity. As the value of the data increases, a greater degree of veracity is required: We must provide more proof to open a bank account than to make friends on Facebook. As a result, there is more trust in bank data than in Facebook data. There is also a growing need to protect marginalized communities.

Emerging technologies and capabilities:

Zero Trust, Blockchain, Data Governance, IoT, Cybersecurity

The image contains a screenshot of Info-Tech's blueprint slide on Zero Trust.


Identity Authenticity

The identity discussion is no longer limited to people or organizations. The development of new technologies, such as the IoT phenomenon, will lead to an explosion of objects, from refrigerators to shipping containers, coming online as well. If all these entities start communicating with each other, standards will be needed to establish who or what they are.















Access badge


Security token

Mobile phone

ID document


Motor skills




Applications use

The IoT market is expected to grow 18% to 14.4 billion in 2022 and 27 billion by 2025.

Source: IoT Analytics, 2022


Data Monetization

Trend 05 Not Many organization know the true value of their data

Data can be valuable if used effectively or dangerous if mishandled. The rise of the data economy has created significant opportunities but also has its challenges. It has become urgent to understand the value of data, which may vary for stakeholders based on their business model and strategy. Organizations first need to understand ownership of their data by establishing a data strategy, then they must improve data maturity by developing a deeper understanding of data value.

94% of enterprises say data is essential to business growth.

Source: Find stack, 2021


Data Monetization

Start developing your data business

  • Blockbuster ran its business well, but Netflix transformed the video rental industry overnight!
  • Big players with data are catching up fast.
  • You don’t have to be a giant to monetize data.
  • Data monetization is probably closer than you think.
  • You simply need to find it, catalog it, and deliver it.

The image contains logos of companies related to data monetization as described in the text above. The companies are Amazon Prime, Netflix, Disney Plus, Blockbuster, and Apple TV.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.


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What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

You Get:

  • An understanding of the nine data and analytics trends and their practical applications.
  • Insights that can help enhance data and analytics capabilities to improve business outcomes.
  • A look at emerging technologies and capabilities that enable value from data.

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