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The Internet of Things (IoT) will bring a whole new meaning to the term Infonomics, which pertains to the economic significance of information. IoT Data as a Service (IoTDaaS) market report offers convenient and cost effective solutions to enterprises of various sizes and domain. IoT DaaS constitutes retrieving, storing and analyzing information and provide customer either of the three or integrated service package depending on the budget and the requirement.Acquiring (capturing and/or licensing), storing, processing, and distributing IoT Data to become a $15B USD business by 2021
Mind Commerce evaluates leading technologies and tools under development, maps benefits to market needs, identifies key solutions, and forecasts market opportunities and demands. This research provides comprehensive analysis of the IoT Data as a Service marketplace. The report includes comprehensive forecasts for the period 2016 – 2021.
Readers of this report will also be interested in the more comprehensive report entitled: IoT Data Management and Analytics Market Outlook & Forecasts 2016 - 2021
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Target Audience:
Network service providers
Systems integration companies
IoT and wireless device manufacturers
Network and device security companies
Data management and analytics companies
Table of Contents from the report are:
1 Introduction
1.1 Research Background
1.2 Research Scope
1.3 Target Audience
2 Executive Summary
3 Overview
3.1 IoT Data in the Emerging Data Economy
3.1.1 IoT Data Strategy
3.1.2 IoT and the Analytics of Things
3.1.3 Specific Strategic Considerations
3.1.3.1 Focus on Data Tiers
3.1.3.2 Maintain a Value-based Approach
3.1.3.3 Foster an Open Development Environment
3.2 Understanding IoT Data
3.2.1 IoT Data vs. other Unstructured Data
3.2.2 Key IoT Data Characteristics
3.2.2.1 IoT Data is Real Time
3.2.2.2 Massive Volumes of IoT Data
3.2.2.3 IoT Data Generates Useful Insights
3.3 IoT Data Management Operations
3.3.1 Basic Data Implementation and Operational Challenges
3.3.1.1 IoT Data Scalability
3.3.1.2 IoT Data Integration
3.3.2 Data Management and Processing Raw Data
3.3.3 Centralized Storage and Decentralized Processing
3.3.4 Accessing and Exchanging IoT Data via APIs
3.3.5 Data Security and Personal Information Privacy
3.4 Monetizing IoT Data and Analytics
3.4.1 IoT Data vs. IoT Data Analytics
3.4.1.1 IoT Data
3.4.1.2 IoT Data Analytics
3.4.2 Key IoT Data Management Monetization Issues
3.4.2.1 IoT Data Ownership
3.4.2.2 IoT Data Care of Custody
3.4.3 Direct vs. Indirect Monetization
3.4.4 Internal vs. External Enterprise IoT Data Monetization
3.4.4.1 Enterprise Data and Analytics: Internal Monetization
3.4.4.2 Enterprise Data and Analytics: External Monetization
3.4.5 Public Data Monetization
3.4.6 Hybrid IoT Monetization
3.4.7 Emerging IoT Data Management and Analytics Marketplace
3.4.7.1 IoT Data as a Service
3.4.7.2 IoT Data Analytics as a Service
3.4.7.3 Decisions as a Service
3.5 Related Monetization Areas
3.5.1 IoT OSS and BSS
3.5.1.1 IoT Operational Support Systems
3.5.1.2 IoT Billing Support Systems
3.5.2 IoT Mediation and Orchestration
3.5.2.1 IoT Mediation and Orchestration Functionality
3.5.2.1.1 IoT Mediation and Orchestration: Virtualization
3.5.2.1.2 IoT Mediation and Orchestration: Identity Management
3.5.2.1.3 Emerging Technologies for IoT Mediation and Orchestration
3.5.2.2 IoT Mediation and Orchestration in Support of Industry Verticals
3.5.2.3 Communication Service Provider Role in IoT Mediation and Orchestration Ecosystem
3.5.2.4 IoT Mediation and Orchestration Roadmap
3.6 Market Outlook for IoT Data Analytics
3.6.1 IoT Data Management is a Ubiquitous Opportunity across Enterprise
3.6.2 IoT Data becomes a Big Revenue Opportunity by 2021
3.6.3 Organizations increasing Adopt Predictive Analytics with IoT Data
3.6.4 Real-time Streaming IoT Data Analytics becoming a Substantial Business Opportunity
3.6.5 Intelligent Strategy and Smart Investment in IoT Data Analytics
3.6.6 IoT Data to Produce Substantial Operational Savings and Generate New Business
3.6.7 Tools Designed Specifically for IoT Data Management and Analytics
3.6.8 IoT Data Management and Analytics Roadmap 2016 to 2025
3.6.8.1 IoT Data Landscape from 2016 to 2018
3.6.8.2 IoT Data Landscape from 2019 to 2020
3.6.8.3 IoT Data Landscape from 2021 to 2025
4 IoT Data as a Service Forecasts 2016 - 2021
4.1 Global IoT Data as a Service 2016 - 2021
4.2 Regional IoT Data as a Service 2016 - 2021
4.3 IoT Data as a Service by Industry Vertical 2016 – 2021
5 Conclusions and Recommendations
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