Global Data as a Service Markets 2020-2025: Focus on Enterprise, Industrial, Public and Government

DUBLIN, Nov. 23, 2020 /PRNewswire/ -- The "Data as a Service Market by Enterprise, Industrial, Public and Government Data Applications and Services 2020 - 2025" report has been added to ResearchAndMarkets.com's offering.

There is considerable competition in the market, happening at a variety of different levels, with features highly variable between vendors. This causes confusion for the enterprise and causes them to often choose two or more providers. Barriers to enterprise adoption of the DaaS model include security concerns, reliability, regulation, vendor lock-in/interoperability, IT management overhead, and other costs.

However, the reasons for implementing DaaS far outweigh the concerns, especially when it comes to IoT data, which must have flexible and scalable platforms for storage, processing, and distribution. Accordingly, enterprise organizations are five times more likely to implement DaaS for machine-generated IoT data than for static data located in corporate repositories or data lakes. The DaaS market must support both static and dynamic data, but the latter will benefit significantly more, especially as edge computing is implemented and real-time data is available.

A surprising number of enterprises do not realize they have options for solutions that involve combinations of different data types including (1) their own data, (2) other companies' data, (3) public data, or a combination of all three. Accordingly, it was not surprising for the publisher of this report to find confusion even for many of those enterprise organizations already considering or implementing Data as a Service.

Another important opportunity area for DaaS is enterprise data syndication, which is the opportunity for companies of various sizes to syndicate (e.g. share and monetize) their data. This is one of the biggest opportunities for the Data as a Service market as a whole. However, there remain challenges above and beyond the core adoption barriers, which include specific security, privacy, and care of custody concerns.

Select Report Findings:

• North America and Western Europe represent the two largest regional markets for DaaS
• IoT DaaS is growing nearly three times as fast as non-IoT DaaS, with much of its streaming data
• Structured data market remains greater than unstructured, but the latter will overtake the former
• Machine-sourced data is growing twice as fast as non-machine data, largely due to IoT apps and services
• Analytics as a Service is the largest opportunity and also one of the fastest-growing segments through 2025
• The DaaS market will receive a huge boost in both usage and revenue from edge computing and real-time data analytics
• Corporate data syndication will become a major drivr of DaaS growth, but data security and privacy challenges will limit the expansion

• DaaS segmentation by Structure, Source, Sector, and Collection type for 2020 to 2025
• Identify leading DaaS companies, strategies, and solutions offering enterprise solutions
• Understand the market dynamics for the Data as a Service market including leading services
• Identify DaaS market drivers and constraints as well as technology challenges and opportunities
• Identify industry vertical Data as a Service market value, globally and regionally, by market segment

Key Topics Covered:

1.0 Executive Summary
1.1 Global Data as a Service Market
1.2 Data as a Service Market by Data Type
1.3 Data as a Service Market by Region

2.0 Data as a Service Technologies
2.1 Cloud Computing and DaaS
2.2 Database Approaches and Solutions
2.2.1 Relational Database Management System
2.2.2 NoSQL
2.2.3 Hadoop
2.2.4 High-Performance Computing Cluster
2.2.5 OpenStack
2.3 Data as a Service and the XaaS Ecosystem
2.4 Open Data Center Alliance
2.5 Market Sizing by Horizontal

3.0 Data as a Service Market
3.1 Market Overview
3.1.1 Understanding Data as a Service
3.1.2 Data Structure
3.1.3 Specialization
3.1.4 Vendors
3.2 Vendor Analysis and Prospects
3.2.1 Large Vendors
3.2.2 Mid-sized Vendors
3.2.3 Small Vendors
3.2.4 Market Sizing
3.3 Data as a Service Market Drivers and Constraints
3.3.1 Data as a Service Market Drivers
3.3.1.1 Business Intelligence and DaaS Integration
3.3.1.2 The Cloud Enabler DaaS
3.3.1.3 XaaS Drives DaaS
3.3.2 Data as a Service Market Constraints
3.3.2.1 Need for Data Integration
3.3.2.2 Issues Relating to Data-as-a-Service Integration
3.4 Barriers and Challenges to DaaS Adoption
3.4.1 Enterprises Reluctance to Change
3.4.2 Responsibility of Data Security Externalized
3.4.3 Security Concerns
3.4.4 Cyber Attacks
3.4.5 Unclear Agreements
3.4.6 Complexity is a Deterrent
3.4.7 Lack of Cloud Interoperability
3.4.8 Service Provider Resistance to Audits
3.4.9 Viability of Third-party Providers
3.4.10 No Move of Systems and Data is without Cost
3.4.11 Lack of Integration Features in the Public Cloud results in Reduced Functionality
3.5 Market Share and Geographic Influence
3.6 Vendors

4.0 Data as a Service Strategies
4.1 General Strategies
4.1.1 Tiered Data Focus
4.1.2 Value-based Pricing
4.1.3 Open Development Environment
4.2 Strategies for Emerging Market Opportunities
4.2.1 Communication Service Providers and DaaS
4.2.2 Internet of Things and Data as a Service
4.2.3 Edge Networks and Data as a Service
4.3 Service Provider Strategies
4.3.1 Telecom Network Operators
4.3.2 Data Center Providers
4.3.3 Managed Service Providers
4.4 Infrastructure Provider Strategies
4.4.1 Enable New Business Models
4.5 Application Developer Strategies

5.0 Data-as-a Service Applications
5.1 Business Intelligence
5.2 Development Environments
5.3 Verification and Authorization
5.4 Reporting and Analytics
5.5 Data as a Service in Healthcare
5.6 Data as a Service and Wearable Technology
5.7 Data as a Service in the Government Sector
5.8 Data as a Service for Media and Entertainment
5.9 Data as a Service for Telecoms
5.10 Data as a Service for Insurance
5.11 Data as a Service for Utilities and Energy Sector
5.12 Data as a Service for Pharmaceuticals
5.13 Data as a Service for Financial Services

6.0 Market Outlook and Future of Data as a Service
6.1 Security Concerns
6.2 Cloud Trends
6.2.1 Hybrid Computing
6.2.2 Multi-Cloud
6.2.3 Cloud Bursting
6.3 Enterprise Leverages own Data and Telecom
6.3.1 Web APIs
6.3.2 SOA and Enterprise APIs
6.3.3 Cloud APIs
6.3.4 Telecom APIs
6.4 Data Federation Emerges for Data as a Service

7.0 Data as a Service Market Analysis and Forecasts 2020 - 2025
7.1 DaaS Market by Sector: Business, Public, and Government
7.1.1 DaaS Market for Public Data
7.1.2 DaaS Market for Business Data (Enterprise and Industrial)
7.1.3 DaaS Market for Government Data
7.2 DaaS Market by Source: Machine and Non-Machine Data
7.3 DaaS Market by Data Collection: IoT and Non-IoT Data
7.4 DaaS Markets by Hosting Type: Private, Public, and Hybrid
7.5 DaaS Markets by Pricing Model
7.6 DaaS Market by Service
7.7 DaaS Markets by Industry Vertical

8.0 Regional DaaS Market Analysis and Forecasts 2020 - 2025

9.0 Conclusions and Recommendations
9.1.1 Data as a Service and IoT
9.1.2 Data as a Service and CSP Data
9.1.3 Data as a Service and Enterprise

10.0 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/h4hwdy

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