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      The Worldwide Data Fabric Industry is Expected to Reach $4.2 Billion by 2026 at a CAGR of 26.3% from 2020

      Research and Markets Logo

      News provided by

      Research and Markets

      Apr 09, 2021, 15:30 ET

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      Share this article


      DUBLIN, April 9, 2021 /PRNewswire/ -- The "Data Fabric Market by Type (Disk-Based, In-Memory), Business Applications (Fraud Detection and Security Management, Customer Experience Management, Business Process Management, GRC Management), Service, Vertical and Region - Global Forecast to 2026" report has been added to ResearchAndMarkets.com's offering.

      The global Data fabric market size to grow from USD 1.0 billion in 2020 to USD 4.2 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 26.3% during the forecast period.

      Various factors such as increasing volume and variety of business data, emerging need for business agility and accessibility, and growing demand for real-time streaming analytics are expected to drive the adoption of the data fabric software and services.

      The COVID-19 pandemic has forced businesses to find new alternatives for speedy recovery and attention to the urgent need to access enough data in crisis times. Disparate data stores hamper the efforts of business leaders to make fully informed decisions. Using a modern data architecture approach called data fabric, Ernst & Young (EY) developed Business Resiliency Data Fabric that enables access to data wherever it lives. Data fabric supports rapid technological change while increasing data entropy. To help alleviate the consequences of COVID-19, Denodo launched the Coronavirus Data Portal (CDP), a collaborative initiative that leverages data virtualization to unify critical datasets originally exposed in different formats from multiple sources and countries and make the unified data open to everyone. Using the CDP and the data virtualization capabilities of the Denodo Platform, pmOne created detailed reports and AI analysis, seamlessly orchestrating all the information streams in the pmOne Share Cockpit. The collaboration of Denodo and pmOne provided the global community with trustworthy, up-to-date data about COVID-19 that can be used to develop new intelligence about COVID-19 and reduce its impact.

      Banks have transitioned to remote sales and service teams and launched digital outreach to customers to make flexible payment arrangements for loans and mortgages. Grocery stores have shifted to online ordering and delivery as their primary business. Schools in many locales have pivoted to 100% online learning and digital classrooms. Doctors have begun delivering telemedicine, aided by more flexible regulation. These approaches have resulted in the rise of volume and variety of business data, the rise in need for business agility and data accessibility, and increasing demand for real-time streaming analytics, contributing to the growth of the data fabric market.

      The software segment to have the largest market size during the forecast period

      The data fabric market has been segmented based on components into software and services. Data fabric makes the movement of data between cloud, storage systems, and data centers smoother, with low latency contributing to the adoption of data fabric software. The services segment, on the other hand, has been bifurcated into consulting services, support and maintenance, and education and training services.

      In-memory data fabric segment to have the highest CAGR during the forecast period

      Based on type of data fabric, the market has been segmented into disk-based data fabric and in-memory data fabric. The adoption of in-memory data fabric is expected to increase significantly in the coming years, owing to the reduction of costs that arise due to the storage and analysis of huge amounts of data.

      Fraud detection and security management segment to account for largest market size during the forecast period

      The data fabric market, by business application, comprises fraud detection and security management; governance, risk and compliance management; customer experience management; sales and marketing management; business process management; and other applications including supply chain management, asset management, and workforce management. Data fabric helps in automating the detection of data anomalies automatically and trigger actions to counter them. This not only minimizes losses but also improves regulatory compliance leading to the adoption of data fabric software for fraud detection and security management

      Among regions, APAC to account for the highest CAGR during the forecast period

      North America is expected to hold the largest market size in the global data fabric market. In contrast, APAC is expected to grow at the highest CAGR during the forecast period due to its growing technology adoption rate. The major countries in APAC that are technology-driven and present major opportunities in terms of investments and revenue include Australia, China, Japan, India, and South Korea. This is the major driving factor for the adoption of Data fabric software in APAC.

      Key Topics Covered:

      1 Introduction

      2 Research Methodology

      3 Executive Summary

      4 Premium Insights
      4.1 Attractive Opportunities in the Data Fabric Market
      4.2 Market, by Application
      4.3 Market, by Region
      4.4 North America Market, by Application and Vertical

      5 Market Overview
      5.1 Market Dynamics
      5.1.1 Drivers
      5.1.1.1 Increasing Volume and Variety of Business Data
      5.1.1.2 Emerging Need for Business Agility and Accessibility
      5.1.1.3 Growing Demand for Real-Time Streaming Analytics
      5.1.2 Restraints
      5.1.2.1 Lack of Awareness About Data Fabric
      5.1.2.2 Lack of Integration with Legacy Systems
      5.1.3 Opportunities
      5.1.3.1 Generating Positive Return on Investment (Roi)
      5.1.3.2 Increasing Adoption of Cloud
      5.1.3.3 Advancement of In-Memory Computing
      5.1.4 Challenges
      5.1.4.1 Disinclination Toward Investment in New Technologies
      5.1.4.2 Lack of Sufficiently Skilled Workforce
      5.2 Industry Trends
      5.2.1 Introduction
      5.2.2 Data Fabric Market: COVID-19 Impact
      5.2.3 Case Study Analysis
      5.2.3.1 Use Case 1: Ducati and Netapp Together Build a Data Fabric Solution to Boost Innovation
      5.2.3.2 Use Case 2: Bloomreach Used Nexla's Solution to Enhance the Customer-Centered Data Approach
      5.2.3.3 Use Case 3: Ingenico Used HPE Ezmeral Data Fabric Solution to Develop a Single Unified Data Platform
      5.2.3.4 Use Case 4: Leading Healthcare Provider Used HPE Ezmeral Data Fabric to Bring Together Disparate Data Sources into One Data Lake
      5.2.3.5 Use Case 5: Ymca of Greater Toronto Leveraged a Data Fabric to Rapidly Deliver a Solution That Allowed Members to Safely Return to Their Facilities During COVID-19

      6 Data Fabric Market, by Component
      6.1 Introduction
      6.1.1 Component: Market Drivers
      6.1.2 Component: COVID-19 Impact
      6.2 Software
      6.3 Services
      6.3.1 Managed Services
      6.3.2 Professional Services
      6.3.2.1 Consulting Services
      6.3.2.2 Support and Maintenance
      6.3.2.3 Education and Training

      7 Data Fabric Market Analysis, by Type of Data Fabric
      7.1 Introduction
      7.1.1 Type of Data Fabric: Market Drivers
      7.1.2 Type of Data Fabric: COVID-19 Impact
      7.2 Disk-Based Data Fabric
      7.3 In-Memory Data Fabric

      8 Data Fabric Market Analysis, by Business Application
      8.1 Introduction
      8.1.1 Business Application: Market Drivers
      8.1.2 Business Application: COVID-19 Impact
      8.2 Fraud Detection and Security Management
      8.3 Governance, Risk, and Compliance Management
      8.4 Customer Experience Management
      8.5 Sales and Marketing Management
      8.6 Business Process Management
      8.7 Other Applications

      9 Data Fabric Market, by Deployment Mode
      9.1 Introduction
      9.1.1 Deployment Mode: Market Drivers
      9.1.2 Deployment Mode: COVID-19 Impact
      9.2 On-Premises
      9.3 Cloud

      10 Data Fabric Market, by Organization Size
      10.1 Introduction
      10.1.1 Organization Size: Market Drivers
      10.1.2 Organization Size: COVID-19 Impact
      10.2 Large Enterprises
      10.3 Small and Medium-Sized Enterprises

      11 Data Fabric Market, by Vertical
      11.1 Introduction
      11.1.1 Vertical: Market Drivers
      11.1.2 Vertical: COVID-19 Impact
      11.2 Data Fabric: Enterprise Use Cases
      11.3 Banking, Financial Services, and Insurance
      11.4 Telecommunications and It
      11.5 Retail and E-Commerce
      11.6 Healthcare and Life Sciences
      11.7 Manufacturing
      11.8 Government
      11.9 Energy and Utilities
      11.10 Media and Entertainment
      11.11 Other Verticals

      12 Data Fabric Market, by Region
      12.1 Introduction
      12.2 North America
      12.3 Europe
      12.4 Asia-Pacific
      12.5 Middle East and Africa
      12.6 Latin America

      13 Competitive Landscape
      13.1 Overview
      13.2 Company Evaluation Quadrant
      13.2.1 Stars
      13.2.2 Emerging Leaders
      13.2.3 Pervasive Players
      13.2.4 Participants
      13.3 Startup/SME Evaluation Quadrant
      13.3.1 Progressive Companies
      13.3.2 Responsive Companies
      13.3.3 Dynamic Companies
      13.3.4 Starting Blocks
      13.4 Competitive Scenario
      13.4.1 Product Launches and Product Enhancements
      13.4.2 Deals
      13.4.3 Others

      14 Company Profiles
      14.1 Introduction
      14.2 Key Players
      14.2.1 IBM
      14.2.2 Oracle
      14.2.3 Informatica
      14.2.4 Talend
      14.2.5 Denodo Technologies
      14.2.6 SAP
      14.2.7 Netapp, Inc.
      14.2.8 Software Ag
      14.2.9 Splunk, Inc.
      14.2.10 HPE
      14.2.11 Dell Technologies
      14.2.12 Teradata
      14.2.13 Precisely
      14.2.14 Global IDS
      14.2.15 Tibco Software
      14.2.16 Idera
      14.3 Start-Up/SME Profiles
      14.3.1 Nexla
      14.3.2 Stardog
      14.3.3 Gluent
      14.3.4 Starburst Data
      14.3.5 Hexstream
      14.3.6 Qomplx
      14.3.7 Cluedin
      14.3.8 Iguazio
      14.3.9 Cinchy

      15 Appendix

      For more information about this report visit https://www.researchandmarkets.com/r/v16fc9

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