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 2022

Data fabric is a distributed data management platform that automatically brings together disparate data sets, both historical and real time and processes them in in an efficient way. Data fabric is an aggregation of multiple big data components which deliver a comprehensive view of customer and business data across an organization. The data fabric market size is expected to grow from USD 653.5 Million in 2017 to USD 2,125.1 Million by 2022, at a Compound Annual Growth Rate (CAGR) of 26.6%. The year 2016 is considered to be the base year while the forecast period is 2017 to 2022.

The objective of the report is to define, describe, and forecast the data fabric market trends on the basis of components, services, data fabric types, business applications, deployment models, organization size, industry verticals, and regions. The objective is also to provide detailed information regarding the major factors influencing the growth of the market (drivers, restraints, opportunities, and challenges).

The research methodology used to estimate and forecast the data fabric market begins with capturing data on key vendor revenues through secondary research sources, such as company websites, Factiva, and Hoovers. Other secondary sources include annual reports, press releases, and investor presentations of companies; white papers and certified publications; and articles from recognized authors, directories, and databases. The vendor offerings are also taken into consideration to determine the market segmentation.

The bottom-up procedure was employed to arrive at the overall market size of the global data fabric market from the revenue of the key players in the market. After arriving at the overall market size, the total market was split into several segments and subsegments, which were then verified through primary research by conducting extensive interviews with key people, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), directors, and executives. The data triangulation and market breakdown procedures were employed to complete the overall market engineering process and to arrive at the exact statistics for all segments and subsegments. The breakdown of the profiles of the primary participants is depicted in the figure below:

To know about the assumptions considered for the study, download the pdf brochure

The data fabric ecosystem comprises vendors such as 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). Other stakeholders of the data fabric market include data fabric platform and software providers, analytics service providers, consulting service providers, IT service providers, resellers, enterprise users, and technology providers.

The target audiences of the data fabric market report are

• Data fabric software vendors
• Cloud Service Providers (CSPs)
• Managed Service Providers (MSPs)
•  System integrators
• Networking companies
• Third-party providers
• Value-Added Resellers (VARs)
• Government agencies
• Consultants/consultancies/advisory firms
• Support and maintenance service providers
• Technology providers

Scope of the Report

The research report categorizes the data fabric market to forecast the revenues and analyze the trends in each of the following subsegments:

By Component

• Software
• Service

By Service

• Managed services
• Professional services
  • Consulting Services
  • Education and training
  • Support and maintenance

By Data Fabric Type

• Disk-based data fabric
• In-memory data fabric

By Business Application

• Fraud detection and security management
• Customer experience management
• Governance, risk, and compliance management
• Sales and marketing management
• Business process management
• Others

By Deployment Model

• On-premises
• Hosted/On-cloud

By Organization Size

• Large enterprises
• Small and Medium Enterprises (SMEs)

By Industry Vertical

• Banking, Financial Services, and Insurance (BFSI)
• Telecommunications and IT
• Retail and ecommerce
• Healthcare and life sciences
• Manufacturing
• Government
• Energy and utilities
• Media and entertainment
• Others

By Region

• North America
• Europe
• Middle East and Africa (MEA)
• Asia Pacific (APAC)
• Latin America

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Geographic Analysis

• Further breakdown of the North American data fabric market
• Further breakdown of the European market
• Further breakdown of the APAC market
• Further breakdown of the MEA market
• Further breakdown of the Latin American market

Company Information

• Detailed analysis and profiling of additional market players

Emerging need for business agility and accessibility along with increasing volume and variety of data are expected to drive the global data fabric market to USD 2.12 billion by 2022

Data fabric is a distributed data management platform that enables organizations to integrate all these data management processes in a single environment. Data fabric solutions bring together disparate data sets—both historical and real-time—automatically and process them in an efficient way. Basically, data fabric is an aggregation of multiple big data components that deliver a comprehensive view of customer and business data across an organization. Data fabric can manage large volumes of data that might be structured, unstructured, or semi-structured.

The collective data that needs to be managed by the end of the decade would be very huge. Data fabric helps 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. Digital transformation aided by real-time analytics, technological advancements in computing power, growing volumes of data, and the cost-effectiveness of data fabric solutions and their secure data assurance have fuelled the growth of data fabric market.

Technology advancement playing a vital role in improving the cloud adoption, eventually creating opportunities for data fabric vendors in the market

Data fabric is gaining traction across various applications is associated with the varying end-user requirements. However, technology advancement also plays a vital role in enhancing the adoption trend, by both companies and customers. Most of the leading analytics technology vendors are now focusing toward the development of a complete cloud-based suite that will have the ability to appraise and enhance its digital properties. it Data fabric can analyze a terabyte of ceaselessly changing data in no time, and can ingest and analyze events from a large number of sources within milliseconds. Analyzing and tracking events from a huge gathering of dynamic assets and generating feedback quickly, opens up new revenue streams and business opportunities that were not possible previously. In-memory computing delivers results faster than the traditional data management tools. The well-known data fabric tools are powered by in-memory platforms, which utilize data from varied sources.

Additionally, Data fabric can generate a positive RoI for organizations in many different ways. Data fabric systems, at their core, improve the efficiency of operations. Analytical systems focus on the effectiveness of business operations. They make it possible to target the best prospects, price risk more accurately, and make better use of available resources. In general, data fabric translates this effectiveness into a positive RoI in one of the several ways. It offers significant throughput with lower latency than the traditional low-latency IP-based middleware.

Market Dynamics

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, 2015–2022 (USD Million)
Table 2 Software: Data Fabric Market Size, By Region, 2015–2022 (USD Million)
Table 3 Services: Market Size, 2015–2022 (USD Million)
Table 4 Managed Services: Market Size, By Region, 2015–2022 (USD Million)
Table 5 Professional Services: Market Size, By Region, 2015–2022 (USD Million)
Table 6 Consulting Services: Market Size, By Region, 2015–2022 (USD Million)
Table 7 Support and Maintenance: Market Size, By Region, 2015–2022 (USD Million)
Table 8 Education and Training:Market Size, By Region, 2015–2022 (USD Million)
Table 9 Data Fabric Market Size, By Type of Data Fabric, 2015–2022 (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, 2015–2022 (USD Million)
Table 13 Fraud Detection and Security Management: Market Size, By Region, 2015–2022 (USD Million)
Table 14 Governance, Risk, and Compliance Management: Market Size, By Region, 2015–2022 (USD Million)
Table 15 Customer Experience Management: Market Size, By Region, 2015–2022 (USD Million)
Table 16 Sales and Marketing Management: Market Size, By Region, 2015–2022 (USD Million)
Table 17 Business Process Management: Market Size, By Region,  2015–2022 (USD Million)
Table 18 Other Applications : Market Size, By Region, 2015–2022 (USD Million)
Table 19 Data Fabric Market Size, By Deployment Model, 2015–2022 (USD Million)
Table 20 On-Premises: Market Size, By Region, 2015–2022 (USD Million)
Table 21 On-Demand: Market Size, By Region, 2015–2022 (USD Million)
Table 22 Data Fabric Market Size, By Organization Size, 2015–2022 (USD Million)
Table 23 Large Enterprises: Market Size, By Region, 2015–2022 (USD Million)
Table 24 Small and Medium-Sized Enterprises: Market Size, By Region, 2015–2022 (USD Million)
Table 25 Data Fabric Market Size, By Industry Vertical, 2015–2022 (USD Million)
Table 26 Banking, Financial Services, and Insurance: Data Fabric Market Size, By Region, 2015–2022 (USD Million)
Table 27 Telecommunications and It: Market Size, By Region, 2015–2022 (USD Million)
Table 28 Retail and Ecommerce: Market Size, By Region, 2015–2022 (USD Million)
Table 29 Healthcare and Life Sciences: Market Size, By Region,  2015–2022 (USD Million)
Table 30 Manufacturing: Market Size, By Region, 2015–2022 (USD Million)
Table 31 Government: Market Size, By Region, 2015–2022 (USD Million)
Table 32 Energy and Utilities: Market Size, By Region, 2015–2022 (USD Million)
Table 33 Media and Entertainment: Market Size, By Region, 2015–2022 (USD Million)
Table 34 Other Verticals:Market Size, By Region, 2015–2022 (USD Million)
Table 35 Data Fabric Market Size, By Region, 2015–2022 (USD Million)
Table 36 North America: Market Size, By Industry Vertical, 2015–2022 (USD Million)
Table 37 North America: Market Size, By Component, 2015–2022 (USD Million)
Table 38 North America: Market Size, By Service, 2015–2022 (USD Million)
Table 39 North America: Market Size, By Professional Service, 2015–2022 (USD Million)
Table 40 North America: Market Size, By Type of Data Fabric, 2015–2022 (USD Million)
Table 41 North America: Market Size, By Business Application, 2015–2022 (USD Million)
Table 42 North America: Market Size, By Deployment Model, 2015–2022 (USD Million)
Table 43 North America: Market Size, By Organization Size, 2015–2022 (USD Million)
Table 44 Europe: Data Fabric Market Size, By Industry Vertical, 2015–2022 (USD Million)
Table 45 Europe: Market Size, By Component, 2015–2022 (USD Million)
Table 46 Europe: Market Size, By Service, 2015–2022 (USD Million)
Table 47 Europe: Market Size, By Professional Service, 2015–2022 (USD Million)
Table 48 Europe: Data Fabric Market Size, By Type of Data Fabric, 2015–2022 (USD Million)
Table 49 Europe: Market Size, By Business Application, 2015–2022 (USD Million)
Table 50 Europe: Market Size, By Deployment Model, 2015–2022 (USD Million)
Table 51 Europe: Market Size, By Organization Size, 2015–2022 (USD Million)
Table 52 Asia Pacific: Data Fabric Market Size, By Industry Vertical, 2015–2022 (USD Million)
Table 53 Asia Pacific: Market Size, By Component, 2015–2022 (USD Million)
Table 54 Asia Pacific: Market Size, By Service, 2015–2022 (USD Million)
Table 55 Asia Pacific: Market Size, By Professional Service, 2015–2022 (USD Million)
Table 56 Asia Pacific: Data Fabric Market Size, By Business Application, 2015–2022 (USD Million)
Table 57 Asia Pacific: Market Size, By Type of Data Fabric, 2015–2022 (USD Million)
Table 58 Asia Pacific: Market Size, By Deployment Model, 2015–2022 (USD Million)
Table 59 Asia Pacific: Market Size, By Organization Size, 2015–2022 (USD Million)
Table 60 Middle East and Africa: Data Fabric Market Size, By Industry Vertical,  2015–2022 (USD Million)
Table 61 Middle East and Africa: Market Size, By Component, 2015–2022 (USD Million)
Table 62 Middle East and Africa: Market Size, By Service, 2015–2022 (USD Million)
Table 63 Middle East and Africa: Market Size, By Professional Service, 2015–2022 (USD Million)
Table 64 Middle East and Africa: Data Fabric Market Size, By Type of Data Fabric,  2015–2022 (USD Million)
Table 65 Middle East and Africa: Market Size, By Business Application, 2015–2022 (USD Million)
Table 66 Middle East and Africa: Market Size, By Deployment Model,  2015–2022 (USD Million)
Table 67 Middle East and Africa: Market Size, By Organization Size,  2015–2022 (USD Million)
Table 68 Latin America: Data Fabric Market Size, By Industry Vertical, 2015–2022 (USD Million)
Table 69 Latin America: Market Size, By Component, 2015–2022 (USD Million)
Table 70 Latin America: Market Size, By Service, 2015–2022 (USD Million)
Table 71 Latin America: Market Size, By Professional Service, 2015–2022 (USD Million)
Table 72 Latin America: Data Fabric Market Size, By Type of Data Fabric, 2015–2022 (USD Million)
Table 73 Latin America: Market Size, By Business Application, 2015–2022 (USD Million)
Table 74 Latin America: Market Size, By Deployment Model, 2015–2022 (USD Million)
Table 75 Latin America: Data Fabric Market Size, By Organization Size, 2015–2022 (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 2017–2022
Figure 11 Market Snapshot on the Basis of Components (2017 vs 2022)
Figure 12 Market Snapshot on the Basis of Types of Data Fabric (2017–2022)
Figure 13 Market Snapshot on the Basis of Services (2017–2022)
Figure 14 Data Fabric Market Snapshot on the Basis of Professional Services (2017–2022)
Figure 15 Market Snapshot on the Basis of Business Applications (2017–2022)
Figure 16 Market Snapshot on the Basis of Deployment Models (2017–2022)
Figure 17 Market Snapshot on the Basis of Organization Size (2017–2022)
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 2017–2022
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

The data fabric market size is expected to grow from USD 653.5 Million in 2017 to USD 2,125.1 Million by 2022, at a Compound Annual Growth Rate (CAGR) of 26.6% during the forecast period. The major growth drivers of the market include increasing volume and variety of business data, emerging need for business agility and accessibility, and growing demand for real-time streaming analytics.

The data fabric market is segmented by type of data fabric, which includes disk-based data fabric and in-memory data fabric. In-memory data fabric is expected to grow at the highest CAGR during the forecast period, due to the growing need of managing and analyzing business data at a faster rate, in real time.

The Banking, Financial Services, and Insurance (BFSI) vertical is expected to hold the largest share of the data fabric market in 2017. The growth is fueled by the growing need of people to simplify their workload related to security, and their increasing dependence on data generated from various IT systems used for financial transactions. The manufacturing vertical is projected to grow at the highest CAGR during the forecast period due to the increasing need to manage data coming from various connected machines and other IT systems, such as supply chain management.

Major business applications for which the data fabric is utilized are fraud detection and security management; governance, risk, and compliance management; customer experience management; sales and marketing management; and business process management. The adoption of data fabric for business process management is expected to increase significantly in the coming years because of the increasing need for resolving business process-related issues in real time and the need for streamlining operations across industries.

Organizations are fast deploying data fabric solutions either on their premises or on-demand. The demand for on-demand or cloud-based data fabric solutions is increasing due to its cost-effective and time-efficient features. Its growth is specifically high in Small and Medium-sized Enterprises (SMEs), where low cost solutions are much required.

The global data fabric market has been segmented on the basis of regions into North America, Asia Pacific (APAC), Europe, Middle East and Africa (MEA), and Latin America to provide a region-specific analysis in the report. The North American region, followed by Europe, is expected to continue being the largest revenue generating region for data fabric vendors for the next 5 years. This is mainly because in the developed economies of the US and Canada, there is a high focus on innovations obtained from Research and Development (R&D) and technology.

The APAC region is expected to be the fastest growing region in the data fabric market because of the increasing adoption of Internet of Things (IoT) and smart technologies, and various government initiatives, such as smart cities across APAC countries, including China and India.

The data fabric market faces challenges, such as disinclination toward investments in new technologies, data security, and lack of sufficiently skilled workforce. Factors such as lack of awareness about data fabric and lack of integration with legacy systems are expected to limit the market growth.

Major vendors that offer data fabric software and services globally 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 Enterprise (US), Teradata Corporation (US), Trifacta (US), Syncsort (US), and K2View (Israel). These vendors have adopted different types of organic and inorganic growth strategies, such as new product launches, partnerships and collaborations, and mergers and acquisitions to expand their offerings in the data fabric market.

The demand for data fabric is increasing as the technology promises faster delivery of business insights as per the requirements of end-users. Data fabric capabilities are being integrated with diverse applications scattered across different verticals of industries, designed to replenish the unique demands of business segments, and are hence driving the growth rate of the data fabric market.

Apart from established players in the industry, the new entrants in the market are introducing advanced data fabric solutions to lure customers across multiple applications

Fraud Detection and Security Management

Fraud detection and security management has been challenging task for most of the organizations. They mainly cover the enterprise risk associated with financial risk, operations risk, or risk associated with an organization’s network efficiency, and preventing company from both internal fraud activities and external fraud activities. Furthermore, 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, and any major risk event can be flagged and is thus taken care 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.

Governance, Risk, and Compliance Management

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. There are various leading vendors providing governance, risk, and compliance management including Oracle, Informatica, and Software AG.

Customer Experience Management

Customer experience management is the process undertaken by an organization to understand the perception of the customer about the brand. Providing the superior customer experience is the major objective of any organization. Customer management is the most important element considered for managing, measuring, and analyzing client performance in order to improve the effectiveness of customer relationship campaigns and improve return on investment. It can help the organizations to predict where the future sales opportunities lie and gain insight into their potential value, thus, enabling them to close more deals sooner and at a lower cost per sale.

Sales & Marketing Optimization

Data fabric fastens the sales by providing the data gathered through sources such as sensors, POS terminals, click streams, and web logs. This information can be used to optimize and accelerate the sales 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 analysing 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.

Business Process Management

Data fabric helps business process management to make organizational workflow in an efficient and more structured manner in order to adopt a changing environment. It is a set of activities which can accomplish the organizational goals. There are various leading players including Oracle, Informatica, IBM, Software AG, and Talend providing business process management. This application helps organizations analyze their current practices, evaluate alternatives, and automate processes which can take advantage from automation, and observe the ongoing performance.

Key questions

• Which are the alternate products and how big is the threat from them?
• Which are the top use cases where data fabric can be implemented for revenue generation through new advancements such as artificial intelligence, IoT, and cloud computing?
• What are the potential opportunities in the adjacent markets, such as Data Lake, big data market and streaming analytics?
• What should be your go-to-market strategy to expand the reach into developing countries across APAC, MEA, and Latin America?

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