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The Big Data as a Service Market is Segmented by Deployment Type (On-premise, Cloud), End-user (Telecom and IT, Energy and Power, BFSI, Healthcare, Retail), and Region.
2018 - 2026
Fastest Growing Market:
In 2020, the Big Data as a Service (BDaaS) market was valued at USD 13.21 billion, and it is expected to reach USD 52.75 billion by 2026, at a CAGR of 26.2% over the forecast period. The evolution of technological tools has enabled solutions to be delivered as a service. Owing to this, Software as a Service (SaaS), Platform as a Service (PaaS), and Data as a Service (DaaS) have emerged as potential growth opportunities for Big Data vendors.
Big Data as a Service (BDaaS) is the delivery of statistical analysis tools or information by an outside provider that helps organizations understand and use insights from large information sets in order to gain a competitive advantage.
|By End User|
|IT and Telecommunication|
|Energy and Power|
|Other End Users|
|Middle East & Africa|
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Private cloud services are explicitly designed for the organization's needs. They are usually offered via a private network or corporate WAN, rather than an open internet source.
Private cloud services allow organizations to set up IT architectures (e.g. by specifying their requirements for security and service-level agreements), and also allow applications hosted in the cloud to integrate with applications that are kept in-house.
In a private cloud, both infrastructure and services are always maintained on a private network, and software and hardware are dedicated solely to the client organization. They ensure that no data is misplaced or lost, and provide the flexibility of control to modify resource configuration according to demand.
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The United States is expected to dominate the regional and global Big Data as a Service market over the forecast period, as most of the major vendors in the market are US-based and the adoption of Big Data services is very high in the regional discrete manufacturing, banking, process manufacturing, professional services, and federal/central government sectors.
According to the Digital Change Survey done by IFS in 2017 to assess the maturity of digital transformation in a range of sectors (such as manufacturing, oil and gas, aviation, construction and contracting), 46% of the companies in all the industries are looking to invest in the Big Data and analytics in the country.
Adoption of Big Data services for enhancing internal efficiency is trending in the country. 43% of companies in the above survey also identified internal process efficiency as the primary driving force behind the digital transformation.
American multinational corporation, Intel is finding significant value in Big Data. The company uses Big Data to develop chips faster, identify manufacturing glitches, and warn about security threats. By adopting Big Data, the company has been able to enable predictive analysis and save around USD 30 million on its quality assurance spend while still improving quality.
The manufacturing sector is also forecast to increase faster than the general economy. According to the MAPI (Manufacturers Alliance for Productivity and Innovation) foundation, production will grow by 2.8% from 2018 to 2021. Further, the rising adoption of SaaS among local SMEs is expected to expand the studied market scope over the forecast period.
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Big Data services have the potential to shift rivalry, opening up numerous new avenues for differentiation and value-added services. The huge expansion of capabilities in the Big Data analytics technology (owing to the availability of open-source tools) may also push the companies to keep up with rivals and give away too much of the improved product performance, an environment that escalates costs and erodes industry profitability. The major Big Data solution providers are acquiring or investing in new startups and technologies that support their overall product offerings.
Some key players in the Big Data as a Service market are IBM, Google, and Oracle. Some key developments in the Big Data as a Service market are:
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET DYNAMICS
4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Increasing Cloud Adoption And Rise In The Data Volume Generated
4.3.2 Increasing Demand For Improving Organization’s Internal Efficiency
4.4 Market Restraints
4.4.1 Data Security Concerns
4.5 Value Chain / Supply Chain Analysis
4.6 Industry Attractiveness - Porter's Five Forces Analysis
4.6.1 Threat of New Entrants
4.6.2 Bargaining Power of Buyers/Consumers
4.6.3 Bargaining Power of Suppliers
4.6.4 Threat of Substitute Products
4.6.5 Intensity of Competitive Rivalry
5. MARKET SEGMENTATION
5.1 By Deployment
5.2 By End User
5.2.1 IT and Telecommunication
5.2.2 Energy and Power
5.2.7 Other End Users
5.3.1 North America
188.8.131.52 Rest of Europe
184.108.40.206 South Korea
220.127.116.11 Rest of Asia-Pacific
5.3.4 Latin America
18.104.22.168 Rest of Latin America
5.3.5 Middle East & Africa
6. COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 IBM Corporation
6.1.2 Microsoft Corporation
6.1.3 Oracle Corporation
6.1.4 SAP SE
6.1.5 Hewlett-Packard Company
6.1.6 SAS Institute Inc.
6.1.7 Accenture PLC
6.1.8 Information Builders Inc.
6.1.9 Google LLC
6.1.10 Amazon Web Services Inc.
6.1.11 Alteryx Ltd
6.1.12 Wipro Ltd
6.1.13 Opera Solutions LLC
6.1.14 Guavus Inc.
7. MARKET INVESTMENT
8. MARKET OPPORTUNITIES AND FUTURE TRENDS
** Subject to Availability