Disk based data fabric refers to simplification and integration of data and data management solutions in order to accelerate digital transformation. A data fabric comprises of various layers in its formation such as endpoints, transport, storage management, data management, ecosystem integration, applications, and services. It helps in delivering consistent and integrated hybrid cloud data services for data visibility and insights, data access & control, and data protection and security.
The vertical segment of the global disk based data fabric market is classified into BFSI, healthcare, manufacturing, IT & telecommunication, media & entertainment, energy & utilities, and others. However, the healthcare sub segment is expected to hold the largest market share of the disk based data fabric market and is also expected to grow at the highest rate over the forecast period owing to the increasing demand for data fabric applications in the healthcare sector.
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Major Key Players:
- Denodo Technologies (U.S.)
- Global IDs (U.S.)
- IBM Corporation (U.S.)
- Informatica (U.S.)
- NetApp Inc. (U.S.)
- Oracle Corporation (U.S.)
- SAP SE (Germany)
- Software AG (Germany)
- Splunk (U.S.)
- Talend (U.S.)
- VMware Inc. (U.S.)
- HP Enterprises (U.S.)
- Teradata Corporation (U.S.)
- Trifacta (U.S.)
- Syncsort Inc. (U.S.)
The global Disk Based Data Fabric Market is expected to grow at a CAGR of approximately 25% during the forecast period 2017-2023.
Market Research Analysis:
North America is estimated to account for the largest share of the market, whereas Europe market is projected to grow at the fastest rate during the forecast period. The North American market is witnessing a rapid growth due to technological advancements and increasing demand for data protection solutions across different industry verticals in this region.
The U.S. holds the majority of market share both in terms of revenue as well as the the growing demand for consistent data management. Also, early adoption of data management systems in North America is likely to lead the market.
The global disk based data fabric market is studied in Asia Pacific, North America, Europe, and Rest of the World. It has been observed that North America is estimated to account for the largest share of the market, whereas Asia Pacific is projected to grow at the fastest rate during the forecast period.
The growth of market in North America is attributed to technological advancements and increased adoption of cloud based technologies across various industry verticals.
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Disk Based Data Fabric Market Segmentation:
The global disk based data fabric market is segmented on the basis of the organization size, application and vertical. The organization size segment is classified small and medium enterprises and large enterprises. However, the large enterprises segment is expected to hold the largest market share of the disk based data fabric market.
Whereas, the small and medium enterprises segment is expected to grow at the highest rate across the globe over the forecast period. This is owing to the increasing demand for data protection services and growing need for mobility of data from small and medium enterprises segment.
- Technology Investors
- Research/Consultancy firms
- Technology Solution Providers
- Government Bodies
- Regulatory agencies
- Cloud service providers
- System integrators
- Technology providers
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Table of Contents
1 Executive Summary
2 Scope of the Report
2.1 Market Definition
2.2 Scope of the Study
2.2.1 Research Objectives
2.2.2 Assumptions & Limitations
2.3 Markets Structure
3 Market Research Methodology
3.1 Research Process
3.2 Secondary Research
3.3 Primary Research
3.4 Forecast Model
List of Tables
Table 1 Global Disk Based Data Fabric Market: By Region, 2017-2023
Table 2 North America Disk Based Data Fabric Market: By Country, 2017-2023
Table 3 Europe Disk Based Data Fabric Market: By Country, 2017-2023
List of Figures
Figure 1 Global Disk Based Data Fabric Market Segmentation
Figure 2 Forecast Methodology
Figure 3 Five Forces Analysis of Global Disk Based Data Fabric Market
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