The "Big Data in Internet of Things: IoT Data Management, Analytics, and Decision Making 2019-2024" report has been added to ResearchAndMarkets.com's offering.
This report evaluates the technologies, companies, and solutions for leveraging Big Data tools and advanced analytics for IoT data processing. Emphasis is placed on leveraging IoT data for process improvement, new and improved products, and ultimately enterprise IoT data syndication. The report includes detailed forecasts for 2019 through 2024.
Data that is uncorrelated and does not have a pre-defined data model and is not organized in a pre-defined manner requires special handling and analytics techniques. The common industry term, big data, represents unstructured data sets that are large, complex, and prohibitively difficult to process using traditional management tools. As the Internet of Things (IoT) progresses, there will an increasingly large amount of unstructured machine data. The growing amount of human-oriented and machine generated data will drive substantial opportunities for AI support of unstructured data analytics solutions.
Big data in IoT is different than conventional IoT and thus will requires more robust, agile and scalable platforms, analytical tools and data storage systems than conventional big data infrastructure. Looking beyond data management processes, IoT data itself will become extremely valuable as an agent of change for product development as well as identification of supply gaps and realization of unmet demands.
Big data and analytics will increase in importance as IoT evolves to become more commonplace. Data generated through sensors embedded in various things/objects will generate massive amounts of unstructured (big) data on real-time basis that holds the promise for intelligence and insights for dramatically improved decision processes.
Big data in IoT is also dissimilar than non-machine related analytics and thus will require more robust, agile and scalable platforms, analytics tools, and data storage systems than conventional infrastructure. Due to this new architecture approach, the need to handle data differently, and the sheer volume of unstructured data, there will be great opportunities for big Data in IoT.
Analytics used in IoT will become an enabler for the entire IoT ecosystem as enterprise begins to take advantage of new business opportunities such as syndicating their own data.
Summary and Conclusions
Emerging Opportunity Areas within Big Data in IoT
- IoT Data Management and Analytics Marketplace
- Decisions as a Service
Evolution of Structured and Unstructured Data Exchange
- Phase One: Limited Data Exchange
- Phase Two: Selective Data Exchange between Industries
- Phase Three: Expanded Data Exchange across Industries and Between Competitors
- Forecasts (global, regional, and by industry) to 2024
- Understand the role and importance of Big Data in IoT
- Identify key market issues and drivers for Big Data in IoT
- Identify leading companies for Big Data and Analytics in IoT
- Understand the emerging vendor ecosystem for Big Data in IoT
- Identify areas for infrastructure, platform, and software investment
Key Topics Covered:
1 Executive Summary
2 Big Data in Internet of Things
2.1 Big Data Framework for IoT
2.2 Need for New Protocols, Platforms, Streaming and Parsing, Software and Analytical Tools
2.2.1 Big Data in IoT will need Unified Logging Layer
2.2.2 Big Data in IoT Data Formats
2.2.3 Big Data in IoT Protocols
2.2.4 Big Data in IoT Protocols for Network Interoperability
2.2.5 Big Data in IoT Data Processing Scalability
2.3 Big Data in IoT Challenges
2.3.2 Data Security and Personal Information Privacy Challenges
3 Big Data in IoT Business Trends and Predictions
3.1 Large Companies Partnerships and M&A
3.2 Big Data as a Service for IoT Becomes Mainstream
3.3 M2M Analytics and Cloud Services will be Early Beneficiaries
3.4 Cybersecurity for Big Data Analytics in IoT
3.5 Flexible and Scalable Revenue Models for Big Data Services
3.6 Big Data Operational Savings and New Business Models
4 Big Data in IoT Vendor Ecosystem
4.1 Cloud based Analytics Platforms for IoT
4.2 Cloud-based Data Storage Service and Management Toolsets
4.3 Big Data Processing for Massive Data Analysis
4.4 Compute, Store, and Analyze Data at the Edge of Networks
4.5 Predictive Platforms and Solutions
4.6 Cloud based Analytics Systems for IoT
4.7 Database System Upgrades and Evolution
4.8 Analytics Platform Upgrades and Evolution
4.9 Real Time DDS and Comprehensive Messaging Platforms
5 Big Data in IoT Market Analysis and Forecasts
5.1 Driving Factors for Big Data in IoT
5.1.1 Consumer IoT
5.1.2 Industrial IoT
5.1.3 Enterprise IoT
5.1.4 Government IoT
5.2 Overall Global Market for Big Data in IoT 2019 - 2025
5.3 Global Big Data Solutions in IoT Market 2019 - 2025
5.4 Global Big Data in IoT Hardware, Software, and Services 2019 - 2025
5.5 Global Big Data in IoT Products and Services 2019 - 2025
5.6 Big Data in IoT by Industry 2019 - 2025
6 Key Companies
- 1010Data (Advance Communication Corp.)
- Actian Corporation
- Allscripts Healthcare Solutions
- Alpine Data Labs
- Anova Data
- Apache Software Foundation
- Apple Inc.
- APTEAN (Formerly CDC Software)
- Athena Health Inc.
- Booz Allen Hamilton
- Bosch Software Innovations: Bosch IoT Suite
- Big Panda
- Bina Technologies Inc.
- Cerner Corporation
- Cisco Systems
- CLC Bio
- Cogito Ltd.
- CRAY Inc.
- Computer Science Corporation (CSC)
- Crux Informatics
- Ctrl Shift
- DataDirect Network
- Data Inc.
- Data Stax
- Dell EMC
- Epic Systems Corporation
- General Electric
- GoodData Corporation
- Grid Gain Systems
- Groundhog Technologies
- HPCC Systems
- HP Enterprise
- Hitachi Data Systems
- Illumina Inc
- Imply Corporation
- Inter Systems Corporation
- IVD Industry Connectivity Consortium-IICC
- Jasper (Cisco Jasper)
- Juniper Networks
- Leica Biosystems (Danaher)
- Mayo Medical Laboratories
- McKesson Corporation
- Medical Information Technology Inc. (MEDITECH)
- MongoDB (Formerly 10Gen)
- MU Sigma
- NTT Data
- Open Text (Actuate Corporation)
- Opera Solutions
- Palantir Technologies Inc.
- Pathway Genomics Corporation
- Perkin Elmer
- Pentaho (Hitachi)
- Qlik Tech
- Quality Systems Inc (QSI)
- Quest Diagnostics Inc.
- Red Hat
- Revolution Analytics
- Roche Diagnostics
- Rocket Fuel Inc.
- SAS Institute
- Selventa Inc.
- Sense Networks
- Shanghai Data Exchange
- Social Cops
- Software AG/Terracotta
- Splice Machine
- Sumo Logic
- Sunquest Information Systems
- Tableau Software
- Tata Consultancy Services
- Think Big Analytics
- Tube Mogul
- Verint Systems
- VMware (Part of EMC)
- Workday (Platfora)
- WuXi NextCode Genomics
For more information about this report visit https://www.researchandmarkets.com/r/3uawjm