Data Fabric Statistics


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Steve Goldstein
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Data Fabric Statistics 2023: Facts about Data Fabric outlines the context of what’s happening in the tech world.

LLCBuddy editorial team did hours of research, collected all important statistics on Data Fabric, and shared those on this page. Our editorial team proofread these to make the data as accurate as possible. We believe you don’t need to check any other resources on the web for the same. You should get everything here only 🙂

Are you planning to form an LLC? Maybe for educational purposes, business research, or personal curiosity, whatever the reason is – it’s always a good idea to gather more information about tech topics like this.

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On this page, you’ll learn about the following:

Top Data Fabric Statistics 2023

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Data Fabric “Latest” Statistics

  • By 2024, 25% of data management suppliers, up from 5% currently, will offer a complete foundation for data fabric.[1]
  • Data fabric efficiency can reduce the time for integration design by 30%, deployment by 30%, and maintenance by 70%.[1]
  • Data fabric can determine what data is being used and make recommendations for further, distinct, and better data, which, in turn, can diminish data-management requirements by up to 70%.[2]
  • The global data-fabric market will hit 3.7 billion from 1.6 billion this year at a CAGR of 22.2% by 2026.[2]
  • In 2018, the data-fabric market size was appreciated at 812.6 million and is predicted to grow at a CAGR of 23.8% from 2019 to 2026, reaching 4,546.9 million by 2026.[3]
  • Asia-Pacific would exhibit the highest data-fabric market CAGR of 26% during 2019-2026.[3]
  • There is no need to go further to understand why 83% of CEOs want their businesses to be more data-driven.[4]
  • 80%–90% of consumers are searching for more reputable businesses to secure their data in nations including the U.S., Canada, China, India, and the UK, among others.[5]
  • Organizations intended to automate 49% of data integration and 37% of data preparation tools by 2020, according to the Data and Analytics Adoption Trends Study.[5]
  • 50% of Gartner client surveys around the topic of AI hold a discussion on the use of graph technology.[6]
  • The HPE Ezmeral data fabric resulted in a 57% smaller cost for data analytics.[7]
  • The HPE Ezmeral data fabric occurred in 52% less time per query and 20X more queries.[7]

Also Read

How Useful is Data Fabric

At its core, data fabric is a holistic approach to data management. It aims to seamlessly integrate data from various sources and formats, providing a unified view of an organization’s data landscape. This can be particularly valuable for companies with disparate data sources spread across different systems and platforms. By consolidating data into a unified fabric, organizations can improve data accessibility, consistency, and quality.

One key benefit of data fabric is its ability to break down data silos. Often, companies face challenges when trying to access and combine data from different departments or systems. Data fabric can help bridge these gaps, enabling organizations to extract insights from a diverse range of data sources. This unified approach can lead to more informed decision-making and a deeper understanding of business operations.

Furthermore, data fabric facilitates data governance and compliance. With organizations handling increasingly large volumes of data, ensuring data security, privacy, and regulatory compliance has become paramount. By centralizing data management processes through a data fabric, companies can establish clear data governance policies, monitor data quality, and ensure compliance with relevant regulations.

From a technological standpoint, data fabric also offers scalability and flexibility. In today’s data-driven world, organizations are constantly generating and collecting vast amounts of data. Data fabric can adapt to changing data volumes and requirements, providing organizations with the agility needed to scale their data operations. This flexibility allows companies to stay ahead of technological advancements and respond to evolving business needs.

Moreover, data fabric can enhance data analytics and artificial intelligence capabilities. By creating a unified data fabric, organizations can simplify data integration and analysis processes, enabling data scientists and analysts to derive valuable insights more efficiently. With the growing adoption of artificial intelligence and machine learning technologies, having a cohesive data fabric in place can optimize AI model training and deployment.

However, despite its many benefits, implementing a data fabric strategy is not without its challenges. Organizations must invest time and resources in designing and implementing a data fabric architecture that aligns with their specific needs and objectives. This process requires careful planning, collaboration across different departments, and a deep understanding of the organization’s data ecosystem.

In conclusion, while data fabric offers significant advantages in terms of data integration, governance, scalability, and analytics, its success ultimately depends on how effectively organizations can leverage this technology to their advantage. By embracing a data fabric strategy and investing in the necessary resources, businesses can enhance their data management capabilities and gain a competitive edge in today’s data-driven world.

Reference


  1. dataconomy – https://dataconomy.com/2022/06/what-is-data-fabric/
  2. internationalbanker – https://internationalbanker.com/technology/data-fabric-simplifying-data-management-in-an-increasingly-data-reliant-world/
  3. alliedmarketresearch – https://www.alliedmarketresearch.com/data-fabric-market
  4. forbes – https://www.forbes.com/sites/tableau/2022/05/17/data-fabrics-bring-the-power-of-data-to-the-people/
  5. fortunebusinessinsights – https://www.fortunebusinessinsights.com/data-fabric-market-105979
  6. gartner – https://www.gartner.com/smarterwithgartner/gartner-top-10-data-and-analytics-trends-for-2021
  7. hpe – https://www.hpe.com/us/en/software/ezmeral-data-fabric.html

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