[175 Pages Report] The overall data fabric market is expected to grow from USD 558.0 million in 2016 to USD 2,125.1 million by 2022, at a CAGR of 26.6% from 2017 to 2022.
The data fabric is a distributed data management platform that enables organizations to integrate various data management processes, including data access, data discovery, data orchestration, data processing, data ingestion, data analytics, and data visualization. It brings together, disparate data sets, both historical and real-time, and automatically processes them in in an efficient way to deliver a comprehensive view of customer and business data across an organization. The base year considered for the study is 2016, and the forecast has been provided for the period between 2017 and 2022.
Data fabric solutions and services provide unmatched opportunities to integrate and analyze the structured, semi-structured and unstructured data sets that otherwise might be disregarded. Not only the business data variety, but also the volume of such data sets is increasing day by day, due to the evolution of digital and smart technologies across varied business functions. Sensor data, geo-location data, machine data, data generated from social media and weblogs, and data from other sources are increasing tremendously on a daily basis. Storing and gaining knowledge from this data is a matter of concern for most organizations. Data fabric helps organizations integrate data from various sources, store large amounts of data, and analyze it seamlessly in one place. Data fabric offers various benefits, such as the ability to derive value from any form of data; the ability to store all types of structured and unstructured data; and centralized access to data via a single, unified view of data across organizations.
During this research study, major players operating in the data fabric market in various regions have been identified, and their offerings, regional presence, and distribution channels have been analyzed through in-depth discussions. Top-down and bottom-up approaches have been used to determine the overall market size. Sizes of the other individual markets have been estimated using the percentage splits obtained through secondary sources such as Hoovers, Bloomberg BusinessWeek, and Factiva, along with primary respondents. The entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews with industry experts such as CEOs, VPs, directors, and marketing executives for key insights (both qualitative and quantitative) pertaining to the market. The figure below shows the breakdown of the primaries on the basis of the company type, designation, and region considered during the research study.
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The data fabric market comprises a network of players involved in the research and product development; system integrator; software and service provider; distribution and sale; and post-sales services. Key players considered in the analysis of the data fabric market are Denodo Technologies (US), Global IDs (US), IBM Corporation (US), Informatica Corporation (US), NetApp (US), Oracle Corporation (US), SAP SE (Germany), Software AG (Germany), Splunk (US), Talend (US), VMware (US), HP Enterprises (US), Teradata Corporation (US), Trifacta (US), Syncsort (US), and K2View (Israel). These Data Fabric Software Vendors are rated and listed by us on the basis of product quality, reliability, and their business strategy. Please visit 360Quadrants to see the vendor listing of Data Fabric Software.
With the given market data, MarketsandMarkets offers customizations as per the companys specific needs. The following customization options are available for the report:
The overall data fabric market is expected to grow from USD 653.5 million in 2017 to USD 2,125.1 million by 2022 at a CAGR of 26.6%. Increasing volume and variety of business data, emerging need for business agility and accessibility, and growing demand for real-time streaming data fabric are the key factors driving the growth of this market.
Data fabric is a distributed data management platform that enables organizations to integrate various data management processes, including data access, data discovery, data orchestration, data processing, data ingestion, data fabric, and data visualization. It brings together, disparate data sets, both historical and real-time, and automatically processes them in in an efficient way to deliver a comprehensive view of customer and business data across an organization.
The data fabric market has been segmented, on the basis of component, types, applications, organization size, deployment model, and industry verticals. APAC is expected to grow at the highest CAGR during the forecast period. With new growth opportunities declining in conventional, strong markets like North America and Europe, a majority of vendors are showing an interest in the APAC region. 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. The companies operating in the APAC region will benefit from the flexible economic conditions, industrialization- and globalization-motivated policies of the governments, as well as the expanding digitalization, which are expected to have a huge impact on the business community in the region. Other countries such as Singapore, Hong Kong, Indonesia, and Malaysia are looking forward to integrating new technologies into their businesses. Fast-growing countries such as China, India, Australia, and Japan are expected to see rapid adoption of data fabric in their mainstream data applications.
Fraud detection and security management has been challenging task for most of the organizations. The data generation process has been increased through various devices and managing security of large amount of data is a complex work. The ability to detect fraud and security threats in real-time is one of the top concerns of organizations across industries. Data fabric plays a major role in detecting anomalies on incoming data and triggering actions immediately. Any flaw in the incoming data can be flagged and taken care of individually. This enables organizations for easy decision-making, helps with customer retention, and assists in making important business decisions in real-time. Data fabric helps to reduce detection time, minimize losses, and improve regulatory reporting. Data fabric makes it easy by using machine learning techniques in order to detect frauds and security threats.
Data fabric fastens the sales procedures by providing the data obtained from the sources such as sensors, machine data, click streams, and web logs. The primaries used to obtain this information could be customers and manufacturers. The sales departments can apply the outcomes from the data obtained to organize their sales exercises and screen the execution of their sales.
Marketing organizations strive to deliver higher ROI. Data fabric enables a more precise segmentation of potential buyers and also facilitates a deeper understanding of those buyers, their needs and motivations by analyzing the data generated from various sources such as social media, call logs, and service forms. Data fabric provides the necessary tools to store and retrieve data in an effective path which help deliver better marketing ROI.Data governance, risk management, and compliance management are the most critical tasks in the data fabric market. The organizational governance process integrates its key elements into coherent process in order to drive corporate governance; the elements include definition and communication control of corporate control, enterprise risk management, key policies, regulatory and compliance management, and operational dashboards and risk scorecards. It helps to reduce the risk and manage the business data. Furthermore, risk management allows organizations to estimate, control, monitor, and mitigate the business and regulatory risks in an organized way. Subsequently, compliance management is an ongoing process of control to meet the requirements enforced by government bodies, industry policies, and regulatory. It helps organization reduce non-compliance and lowers the cost.
The lack of awareness about data fabric and lack of integration with legacy systems are the major factors restraining the growth of the data fabric market. Data fabric solutions and services help organizations manage huge data sets. In spite of a lot of eye-grabbing of data fabric in the recent past, the actual adoption of data fabric in business decision-making is still low and not very easily understood by many. The major limitation of data fabric is the lack of awareness about the newer data storage and analytics techniques. End-users in various verticals lack understanding about the benefits of data fabric, as well as, about how it works. This can restrain the companies to invest in data fabric. Data fabric is yet to be embraced by many large enterprises and most of the Small and Medium-Sized Enterprises (SMEs), to leverage its potential for transforming business processes. Therefore, education and lack of awareness may be data fabrics major restraints.
Key players in the market include Denodo Technologies (U.S.), Global IDs (U.S.), IBM Corporation (U.S.), Informatica Corporation (U.S.), NetApp (U.S.), Oracle Corporation (U.S.), SAP SE (Germany), Software AG (Germany), Splunk (U.S.), Talend (U.S.), VMware (U.S.), HP Enterprises (U.S.), Teradata Corporation (U.S.), Trifacta (U.S.), Syncsort (U.S.), and K2View (Israel). These players are increasingly undertaking mergers and acquisitions, and product launches to develop and introduce new technologies and products in the market.
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Table of Contents
1 Introduction (Page No. - 17)
1.1 Objectives of the Study
1.2 Market Definition
1.3 Market Scope
1.4 Years Considered for the Study
1.5 Currency
1.6 Stakeholders
2 Research Methodology (Page No. - 21)
2.1 Research Data
2.1.1 Secondary Data
2.1.2 Primary Data
2.1.2.1 Breakdown of Primaries
2.1.2.2 Key Industry Insights
2.2 Market Size Estimation
2.3 Microquadrant Research Methodology
2.3.1 Vendor Inclusion Criteria
2.4 Research Assumptions
2.5 Limitations
3 Executive Summary (Page No. - 29)
4 Premium Insights (Page No. - 36)
4.1 Attractive Market Opportunities in the Data Fabric Market
4.2 Market: Market Share Across Various Regions
4.3 Market: Industry Verticals and Regions
4.4 Life Cycle Analysis, By Region, 2017
5 Market Overview and Industry Trends (Page No. - 40)
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Increasing Volume and Variety of Business Data
5.2.1.2 Emerging Need for Business Agility and Accessibility
5.2.1.3 Growing Demand for Real-Time Streaming Analytics
5.2.2 Restraints
5.2.2.1 Lack of Awareness About Data Fabric
5.2.2.2 Lack of Integration With Legacy Systems
5.2.3 Opportunities
5.2.3.1 Generating Positive Return on Investment (RoI)
5.2.3.2 Increasing Adoption of Cloud
5.2.3.3 Advancement of In-Memory Computing
5.2.4 Challenges
5.2.4.1 Disinclination Toward Investment in New Technologies
5.2.4.2 Lack of Sufficiently Skilled Workforce
5.3 Industry Trends
5.3.1 Introduction
5.3.2 Data Fabric Architecture
5.3.3 Data Fabric Use Cases
5.3.3.1 Introduction
5.3.3.2 Use Case 1: K2View (Telecommunications Sector | South America)
5.3.3.3 Use Case 2: Veritas (Sky PLC | Entertainment |Europe)
5.3.3.4 Use Case 3: Gridgain Systems, Inc. (Cyber Dust | IT and Telecommunication | North America)
6 Data Fabric Market Analysis, By Component (Page No. - 49)
6.1 Introduction
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 Market Analysis, By Type of Data Fabric (Page No. - 57)
7.1 Introduction
7.2 Disk-Based Data Fabric
7.3 In-Memory Data Fabric
8 Data Fabric Market Analysis, By Business Application (Page No. - 61)
8.1 Introduction
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 Market Analysis, By Deployment Model (Page No. - 67)
9.1 Introduction
9.2 On-Premises
9.3 On-Demand
10 Data Fabric Market Analysis, By Organization Size (Page No. - 71)
10.1 Introduction
10.2 Large Enterprises
10.3 Small and Medium-Sized Enterprises
11 Data Fabric Market Analysis, By Industry Vertical (Page No. - 75)
11.1 Introduction
11.2 Banking, Financial Services, and Insurance
11.3 Telecommunications and It
11.4 Retail and Ecommerce
11.5 Healthcare and Life Sciences
11.6 Manufacturing
11.7 Government
11.8 Energy and Utilities
11.9 Media and Entertainment
11.10 Other Verticals
12 Geographic Analysis (Page No. - 83)
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 (Page No. - 107)
13.1 Introduction
13.1.1 Dynamic
13.1.2 Innovators
13.1.3 Vanguards
13.1.4 Emerging
13.2 Microquadrant
13.3 Product Offering
13.4 Business Strategy
14 Company Profiles (Page No. - 111)
(Business Overview, Products & Services, Key Insights, Recent Developments, SWOT Analysis, MnM View)*
14.1 Denodo Technologies
14.2 Global IDS
14.3 International Business Machines Corporation
14.4 Informatica
14.5 NetApp, Inc.
14.6 Oracle Corporation
14.7 SAP SE
14.8 Software AG
14.9 Splunk, Inc.
14.10 Syncsort
14.11 Talend S.A.
14.12 VMware, Inc.
14.13 Hewlett Packard Enterprise Company
14.14 Teradata Corporation
14.15 K2View
*Details on Business Overview, Products & Services, Key Insights, Recent Developments, SWOT Analysis, MnM View Might Not Be Captured in Case of Unlisted Companies.
15 Appendix (Page No. - 166)
15.1 Insights of Industry Experts
15.2 Discussion Guide
15.3 Knowledge Store: Marketsandmarkets Subscription Portal
15.4 Available Customization
15.5 Related Reports
15.6 Author Details
List of Tables (75 Tables)
Table 1 Data Fabric Market Size, By Component, 20152022 (USD Million)
Table 2 Software: Data Fabric Market Size, By Region, 20152022 (USD Million)
Table 3 Services: Market Size, 20152022 (USD Million)
Table 4 Managed Services: Market Size, By Region, 20152022 (USD Million)
Table 5 Professional Services: Market Size, By Region, 20152022 (USD Million)
Table 6 Consulting Services: Market Size, By Region, 20152022 (USD Million)
Table 7 Support and Maintenance: Market Size, By Region, 20152022 (USD Million)
Table 8 Education and Training:Market Size, By Region, 20152022 (USD Million)
Table 9 Data Fabric Market Size, By Type of Data Fabric, 20152022 (USD Million)
Table 10 Disk-Based Data Fabric: Market Size, By Region, 2015-2022 (USD Million)
Table 11 In-Memory Data Fabric: Market Size, By Region, 2015-2022 (USD Million)
Table 12 Data Fabric Market Size, By Business Application, 20152022 (USD Million)
Table 13 Fraud Detection and Security Management: Market Size, By Region, 20152022 (USD Million)
Table 14 Governance, Risk, and Compliance Management: Market Size, By Region, 20152022 (USD Million)
Table 15 Customer Experience Management: Market Size, By Region, 20152022 (USD Million)
Table 16 Sales and Marketing Management: Market Size, By Region, 20152022 (USD Million)
Table 17 Business Process Management: Market Size, By Region, 20152022 (USD Million)
Table 18 Other Applications : Market Size, By Region, 20152022 (USD Million)
Table 19 Data Fabric Market Size, By Deployment Model, 20152022 (USD Million)
Table 20 On-Premises: Market Size, By Region, 20152022 (USD Million)
Table 21 On-Demand: Market Size, By Region, 20152022 (USD Million)
Table 22 Data Fabric Market Size, By Organization Size, 20152022 (USD Million)
Table 23 Large Enterprises: Market Size, By Region, 20152022 (USD Million)
Table 24 Small and Medium-Sized Enterprises: Market Size, By Region, 20152022 (USD Million)
Table 25 Data Fabric Market Size, By Industry Vertical, 20152022 (USD Million)
Table 26 Banking, Financial Services, and Insurance: Data Fabric Market Size, By Region, 20152022 (USD Million)
Table 27 Telecommunications and It: Market Size, By Region, 20152022 (USD Million)
Table 28 Retail and Ecommerce: Market Size, By Region, 20152022 (USD Million)
Table 29 Healthcare and Life Sciences: Market Size, By Region, 20152022 (USD Million)
Table 30 Manufacturing: Market Size, By Region, 20152022 (USD Million)
Table 31 Government: Market Size, By Region, 20152022 (USD Million)
Table 32 Energy and Utilities: Market Size, By Region, 20152022 (USD Million)
Table 33 Media and Entertainment: Market Size, By Region, 20152022 (USD Million)
Table 34 Other Verticals:Market Size, By Region, 20152022 (USD Million)
Table 35 Data Fabric Market Size, By Region, 20152022 (USD Million)
Table 36 North America: Market Size, By Industry Vertical, 20152022 (USD Million)
Table 37 North America: Market Size, By Component, 20152022 (USD Million)
Table 38 North America: Market Size, By Service, 20152022 (USD Million)
Table 39 North America: Market Size, By Professional Service, 20152022 (USD Million)
Table 40 North America: Market Size, By Type of Data Fabric, 20152022 (USD Million)
Table 41 North America: Market Size, By Business Application, 20152022 (USD Million)
Table 42 North America: Market Size, By Deployment Model, 20152022 (USD Million)
Table 43 North America: Market Size, By Organization Size, 20152022 (USD Million)
Table 44 Europe: Data Fabric Market Size, By Industry Vertical, 20152022 (USD Million)
Table 45 Europe: Market Size, By Component, 20152022 (USD Million)
Table 46 Europe: Market Size, By Service, 20152022 (USD Million)
Table 47 Europe: Market Size, By Professional Service, 20152022 (USD Million)
Table 48 Europe: Data Fabric Market Size, By Type of Data Fabric, 20152022 (USD Million)
Table 49 Europe: Market Size, By Business Application, 20152022 (USD Million)
Table 50 Europe: Market Size, By Deployment Model, 20152022 (USD Million)
Table 51 Europe: Market Size, By Organization Size, 20152022 (USD Million)
Table 52 Asia Pacific: Data Fabric Market Size, By Industry Vertical, 20152022 (USD Million)
Table 53 Asia Pacific: Market Size, By Component, 20152022 (USD Million)
Table 54 Asia Pacific: Market Size, By Service, 20152022 (USD Million)
Table 55 Asia Pacific: Market Size, By Professional Service, 20152022 (USD Million)
Table 56 Asia Pacific: Data Fabric Market Size, By Business Application, 20152022 (USD Million)
Table 57 Asia Pacific: Market Size, By Type of Data Fabric, 20152022 (USD Million)
Table 58 Asia Pacific: Market Size, By Deployment Model, 20152022 (USD Million)
Table 59 Asia Pacific: Market Size, By Organization Size, 20152022 (USD Million)
Table 60 Middle East and Africa: Data Fabric Market Size, By Industry Vertical, 20152022 (USD Million)
Table 61 Middle East and Africa: Market Size, By Component, 20152022 (USD Million)
Table 62 Middle East and Africa: Market Size, By Service, 20152022 (USD Million)
Table 63 Middle East and Africa: Market Size, By Professional Service, 20152022 (USD Million)
Table 64 Middle East and Africa: Data Fabric Market Size, By Type of Data Fabric, 20152022 (USD Million)
Table 65 Middle East and Africa: Market Size, By Business Application, 20152022 (USD Million)
Table 66 Middle East and Africa: Market Size, By Deployment Model, 20152022 (USD Million)
Table 67 Middle East and Africa: Market Size, By Organization Size, 20152022 (USD Million)
Table 68 Latin America: Data Fabric Market Size, By Industry Vertical, 20152022 (USD Million)
Table 69 Latin America: Market Size, By Component, 20152022 (USD Million)
Table 70 Latin America: Market Size, By Service, 20152022 (USD Million)
Table 71 Latin America: Market Size, By Professional Service, 20152022 (USD Million)
Table 72 Latin America: Data Fabric Market Size, By Type of Data Fabric, 20152022 (USD Million)
Table 73 Latin America: Market Size, By Business Application, 20152022 (USD Million)
Table 74 Latin America: Market Size, By Deployment Model, 20152022 (USD Million)
Table 75 Latin America: Data Fabric Market Size, By Organization Size, 20152022 (USD Million)
List of Figures (76 Figures)
Figure 1 Market Segmentation
Figure 2 Regional Scope
Figure 3 Data Fabric Market: Research Design
Figure 4 Breakdown of Primary Interviews: By Company, Designation, and Region
Figure 5 Data Triangulation
Figure 6 Market Size Estimation Methodology: Bottom-Up Approach
Figure 7 Market Size Estimation Methodology: Top-Down Approach
Figure 8 Evaluation Criteria
Figure 9 Data Fabric Market: Assumptions
Figure 10 Data Fabric Market is Poised to Witness Growth in the Global Market During 20172022
Figure 11 Market Snapshot on the Basis of Components (2017 vs 2022)
Figure 12 Market Snapshot on the Basis of Types of Data Fabric (20172022)
Figure 13 Market Snapshot on the Basis of Services (20172022)
Figure 14 Data Fabric Market Snapshot on the Basis of Professional Services (20172022)
Figure 15 Market Snapshot on the Basis of Business Applications (20172022)
Figure 16 Market Snapshot on the Basis of Deployment Models (20172022)
Figure 17 Market Snapshot on the Basis of Organization Size (20172022)
Figure 18 Data Fabric Market Snapshot on the Basis of Industry Verticals (2017 vs 2022)
Figure 19 Increasing Volume and Variety of Business Data is the Major Factor Contributing to the Growth of the Data Fabric Market
Figure 20 North America is Expected to Hold the Largest Market Share in 2017
Figure 21 Banking, Financial Services, and Insurance Vertical and North America are Expected to Have the Largest Market Size in 2017
Figure 22 North America and Europe to Enter Exponential Growth Phase During 20172022
Figure 23 Data Fabric Market: Drivers, Restraints, Opportunities, and Challenges
Figure 24 Market Architecture
Figure 25 Services Segment is Expected to Have A Higher CAGR During the Forecast Period
Figure 26 Managed Services Segment is Expected to Have A Higher CAGR During the Forecast Period
Figure 27 Education and Training is Expected to Have the Highest CAGR During the Forecast Period
Figure 28 In-Memory Data Fabric is Expected to Have A Higher CAGR During the Forecast Period
Figure 29 Business Process Management Segment is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 30 On-Demand Deployment Model is Expected to Have A Higher CAGR During the Forecast Period
Figure 31 Small and Medium-Sized Enterprises Segment is Expected to Have A Higher CAGR During the Forecast Period
Figure 32 Manufacturing Vertical is Expected to Have the Highest CAGR During the Forecast Period
Figure 33 Asia Pacific is Expected to Have the Highest CAGR During the Forecast Period
Figure 34 North America is Projected to Have the Largest Market Share in the Data Fabric Market
Figure 35 North America Market Snapshot
Figure 36 Asia Pacific Market Snapshot
Figure 37 Denodo Technologies: Product Offering Scorecard
Figure 38 Denodo Technologies: Business Strategy Scorecard
Figure 39 Global IDS: Product Offering Scorecard
Figure 40 Global IDS: Business Strategy Scorecard
Figure 41 International Business Machines Corporation: Company Snapshot
Figure 42 International Business Machines Corporation: Product Offering Scorecard
Figure 43 International Business Machines Corporation: Business Strategy Scorecard
Figure 44 Informatica: Product Offering Scorecard
Figure 45 Informatica: Business Strategy Scorecard
Figure 46 NetApp, Inc.: Company Snapshot
Figure 47 NetApp, Inc.: Product Offering Scorecard
Figure 48 NetApp, Inc.: Business Strategy Scorecard
Figure 49 Oracle Corporation: Company Snapshot
Figure 50 Oracle Corporation: Product Offering Scorecard
Figure 51 Oracle Corporation: Business Strategy Scorecard
Figure 52 SAP SE: Company Snapshot
Figure 53 SAP SE: Product Offering Scorecard
Figure 54 SAP SE: Business Strategy Scorecard
Figure 55 Software AG: Company Snapshot
Figure 56 Software AG: Product Offering Scorecard
Figure 57 Software AG: Business Strategy Scorecard
Figure 58 Splunk, Inc.: Company Snapshot
Figure 59 Splunk, Inc.: Product Offering Scorecard
Figure 60 Splunk, Inc.: Business Strategy Scorecard
Figure 61 Syncsort: Product Offering Scorecard
Figure 62 Syncsort: Business Strategy Scorecard
Figure 63 Talend S.A.: Company Snapshot
Figure 64 Talend S.A.: Product Offering Scorecard
Figure 65 Talend S.A.: Business Strategy Scorecard
Figure 66 VMware, Inc.: Company Snapshot
Figure 67 VMware, Inc.: Product Offering Scorecard
Figure 68 VMware, Inc.: Business Strategy Scorecard
Figure 69 Hewlett Packard Enterprise Company: Company Snapshot
Figure 70 Hewlett Packard Enterprise Company: Product Offering Scorecard
Figure 71 Hewlett Packard Enterprise Company: Business Strategy Scorecard
Figure 72 Teradata Corporation: Company Snapshot
Figure 73 Teradata Corporation: Product Offering Scorecard
Figure 74 Teradata Corporation: Business Strategy Scorecard
Figure 75 K2View: Product Offering Scorecard
Figure 76 K2View: Business Strategy Scorecard
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