Global IoT Data Management and Analytics Market 2021-2026: Flexible and Scalable Revenue Model will be Most Successful

DUBLIN, March 8, 2021 /PRNewswire/ -- The "IoT Data Management and Analytics Market by Technology, Infrastructure, Deployment Model (Cloud vs. Premise), Solutions, Applications and Services in Industry Verticals 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.

This report evaluates the market for IoT data management and analytics. The report analyzes key challenges and opportunities such as managing IoT data based on ownership, care of custody, and usage rights.

The report assesses the opportunity for IoT data as a service and IoT-driven decisions as a service. It includes forecasts by technology, infrastructure, applications and services for both static and real-time data from 2021 through 2026.

The report evaluates substantial market opportunities involving IoT data collection, storage, analytics and visualization. It identifies how real-time, streaming data IoT business data becomes highly valuable when it can be put into context and processes as it will facilitate completely new product and service offerings.

This facilitates new opportunities for supporting software, storage and analytics solutions. The report includes analysis of technologies, tools and platforms for collecting, storing and processing IoT data.

Industrial IoT (IIoT) and enterprise IoT deployments in particular will generate a substantial amount of data, most of which will be of the unstructured variety, requiring next-generation data analytics tools and techniques. For example, manufacturing processes produce vast amounts of machine-generated data, most of which is unstructured and from disparate sources and formats.

Accordingly, there is a need for uniform data management processes and the use of big data analytics tools and techniques. While much of this data will be very useful for longer-term analytics, significant value will be realized from real-time processing such as centralized versus distributed manufacturing decisions.

It is important to recognize that intelligence within IoT networks is not inherent but rather must be carefully planned. IoT market elements will be found embedded within software programs, chipsets, and platforms as well as human-facing devices, which may rely upon a combination of local and cloud-based intelligence.

Just like the human nervous system, IoT networks will have both autonomic and cognitive functional components that provide intelligent control as well as nervous system-like end-points that provide signaling (detection and triggering of communications) and connectivity. Each of these system components are sources of potentially useful data, which must be analyzed to determine if useful information may be realized.

Select Report Findings:

• Real-time monitoring in healthcare will reach $11B by 2026
• Improved operations in the retail sector will reach $2.8B by 2026
• Global data collection solutions market to reach $7.3B by 2026
• Global IoT data support software market to reach $23.4B by 2026
• Global IoT data storage solutions market to reach $13.6B by 2026
• Global IoT data analytics solutions market to reach $16B by 2026
• Leading industry verticals are healthcare, manufacturing and retail
• The Asia Pac region to lead the IoT data analytics market through 2026
• APAC real-time IoT data analytics solutions alone to reach $6722M by 2026

Key Topics Covered:

1 Executive Summary

2 IoT Data Management and Analytics Market Overview
2.1 IoT Data Management and Analytics Market Ecosystem
2.2 Overall IoT Data Management and Analytics Market Opportunity
2.3 Regional IoT Data Management and Analytics Market Outlook

3 Introduction to IoT Data Management and Analytics
3.1 IoT Data in the Emerging Data Economy
3.2 Unique IoT Data Management Requirements
3.3 IoT Data Management Operations
3.4 Monetizing IoT Data and Analytics
3.5 IoT Data Operational Requirements
3.6 Market Outlook for IoT Data Analytics

4 IoT Data Management and Analytics Market Dynamics
4.1 IoT Data Management Drivers
4.2 IoT Data Management Challenges

5 IoT Data Platform Providers
5.1 Amdocs
5.2 AppDirect, Inc.
5.3 City Data Exchange
5.4 Horadata
5.5 Interdigital
5.6 Optiva (formerly RedKnee)
5.7 Terbine
5.8 Tilepay

6 Technologies Enabling IoT Data
6.1 Present Technologies are Not Suitable for IoT Data
6.2 Technologies Specially Developed for IoT Data

7 Global IoT Data Market Analysis and Forecasts 2021 - 2026
7.1 Overall IoT Data Market Considerations and Outlook
7.2 Market Outlook and Forecasts for IoT Data 2021 - 2026
7.3 IoT Data Infrastructure ROI Assessment
7.3.1 Factors Determining ROI for IoT

8 Vendor Analysis
8.1 Key Vendor Trends in IoT Data
8.2 Large Companies to Lead through M&A and Partnerships
8.2.1 Early Beneficiaries: Established Companies in Analytics and Cloud Services
8.2.2 Flexible and Scalable Revenue Model will be Most Successful
8.3 Select Company Analysis
8.3.1 Recent Development of Major Players
8.3.2 Accenture
8.3.3 AGT International
8.3.4 Bosch Software Innovations
8.3.5 Capgemini
8.3.6 Cisco Systems, Inc.
8.3.7 GE Digital
8.3.8 Google
8.3.9 Intel Corporation
8.3.10 Lynx Software Technologies, Inc.
8.3.11 Maana, Inc.
8.3.12 Microsoft Corporation
8.3.13 MongoDB Inc.
8.3.14 ParStream (now fully part of Cisco)
8.3.15 PTC
8.3.16 RIOT
8.3.17 SAP SE
8.3.18 SQLstream, Inc. (Guavus)
8.3.19 Tellient
8.3.20 Teradata Corporation
8.3.21 Wind River

9 IoT Data Management and Analytics Market Benefits, Capabilities, and Case Studies
9.1 IoT Data Analytics Solutions Benefits
9.2 Key Capabilities for Data Management in IoT
9.3 IoT Data Analytics Case Studies
9.3.1 AWS IoT Case Study
9.3.2 Predictive Analytics for Supply Chain Management
9.3.3 American Instrumentation implements Azure-based IoT Solution
9.3.4 IoT-Commercial Real Estate Management

10 Conclusions and Recommendations

11 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/20r05z

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