The report "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", 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 solutions and services.
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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 services segment to hold higher CAGR during the forecast period
Based on components, the data fabric market is segmented 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. The services segment is expected to account for higher CAGR during the forecast as services are required by organizations to bring about effective data fabric implementation strategies that can be handled by third-party companies, and the organizations can concentrate on their core businesses.
The large enterprises segment to hold largest market size during the forecast period
The Data fabric market has been segmented by organization size into large enterprises and SMEs. The market share of large enterprises is higher; however, the market for SMEs is expected to register a higher CAGR during the forecast period. The demand for data fabric is accelerating due to its cost-effective and time-efficient feature; its growth is specifically high in large enterprises, where low-cost solutions are in demand.
The cloud segment to have higher CAGR during the forecst period
Based on deployment mode, the market has been segmented into on-premises and cloud. The on-premises segment is expected to hold largest market size while the cloud segment is expected to account for higher CAGR during the forecast period due to the ease of using only the functionalities without knowing the implementation. The cloud deployment mode is being widely adopted by enterprises in all regions where data security is a major concern.
Banking, Financial services, and Insurance segment to have the largest market size during the forecast period
The Data fabric market by vertical has been categorized into 9 different verticals, namely, BFSI, telecommunications and IT, retail and e-commerce, healthcare and life sciences, manufacturing, government, energy and utilities, media and entertainment, and others. The other verticals comprise transportation and logistics, travel and hospitality, and education. The market size of BFSI segment is expected to be the largest as data fabric can help financial institutions by providing a flexible means for ingesting data from enterprise and external systems, storing data securely, generating insights, and providing access through data services (APIs) while maintaining cost efficiency. This leads to its adoption in the BFSI sector.
North America to hold largest market size during the forecast period
North America has been at the forefront in driving the major portion of the revenue generated by the data management and analytics vendors. State-of-the-art infrastructure, high funding opportunities, widespread customer base across several industries, and availability of a highly-skilled workforce have been major contributors to the innovation and early adoption of various technologies such as big data and related technologies, analytics, and IoT. Rapid digitalization across industry verticals, increasing adoption of IoT-enabled technologies, and technological advancements are fueling the adoption of data fabric in North America.
Major vendors in the global data fabric market include Denodo Technologies (US), Global IDs (US), IBM Corporation (US), Informatica (US), NetApp (US), Oracle Corporation (US), SAP SE (Germany), Software AG (Germany), Splunk (US), Talend (US), Dell Technologies (US), HP Enterprise (US), Teradata Corporation (US), TIBCO Software (US), Precisely (US), Idera (US), Nexla (US), Stardog (US), Gluent (US), Starburst Data (US), HEXstream (US), QOMPLX (US), CluedIn (Denmark), Iguazio (Israel), and Cinchy (Canada).
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