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PUBLISHER: Mind Commerce | PRODUCT CODE: 1131100

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PUBLISHER: Mind Commerce | PRODUCT CODE: 1131100

Big Data in IoT by Technology, Infrastructure, Solutions, and Industry Verticals 2022 - 2027

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Overview:

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 2022 through 2027.

Select Report Findings:

  • The overall global market for big data in IoT will reach $63.8 billion by 2027
  • Data analytics is the largest segment by product and service in the big data IoT market
  • Big data in IoT as a service will reach $8.1 billion by 2027 with North America leading the market
  • Storage of big data in IoT will reach $19.2 billion by 2027, driven by low-cost cloud-based solutions
  • Big data in IoT within the government sector will exceed $7.23 billion by 2027, fueled by military and public safety initiatives
  • Financial services, government, telecom, retail, healthcare, manufacturing, building automation, consumer electronics, and transport and cargo are some of the major industry verticals for the big data in the IoT market

Data that is uncorrelated and does not have a pre-defined data model and is not organized in a predefined 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) continues to evolve, there will be 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.

The business has a great potential and it can be seen with the trend of big companies such as Cisco, Bosch, IBM, Intel, Google, Amazon, AT&T entering the business of big data analytics in IoT either through acquisition or partnering with companies and startups developing various tools, platforms and APIs in big data.

Big data in IoT is different from conventional IoT and thus will require more robust, agile and scalable platforms, analytical tools and data storage systems than conventional big data infrastructure. Generation of data is often at very high volumes for many applications and it manifests in many forms. This facilitates the need to develop new platforms and systems.

Companies such as Treasure Data (Softbank), have developed unified logging layer Fluentd, JSON coming up as a Java-based lightweight data interchange platform and DDS helping in real-time data processing and lightweight protocols are some of the great developments happening towards developing dedicated big data infrastructure for IoT.

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 used in IoT will become an enabler for the entire IoT ecosystem and business as a whole as enterprises begin to syndicate their own data.

Artificial Intelligence (AI) further enhances the ability of big data analytics and IoT platforms to provide value to each of these market segments. The use of AI for decision-making in IoT and data analytics will be crucial for efficient and effective decision-making, especially in the area of streaming data and real-time analytics associated with edge computing networks.

Real-time data will be a key value proposition for all use cases, segments, and solutions. The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic. In many cases, the data itself, and actionable information will be the service.

Companies in Report:

  • 1010Data (Advance Communication Corp.)
  • Accenture
  • Actian Corporation
  • AdvancedMD
  • Alation
  • Allscripts Healthcare Solutions
  • Alpine Data Labs
  • Alteryx
  • Amazon
  • Apache Software Foundation
  • Apple Inc.
  • APTEAN (Formerly CDC Software)
  • AthenaHealth Inc.
  • Attunity
  • BGI
  • Big Panda
  • Booz Allen Hamilton
  • Bosch
  • Capgemini
  • CARTO
  • Cerner Corporation
  • Cisco Systems
  • Climate Corporation
  • Cloudera
  • Cogito Ltd.
  • Computer Science Corporation
  • Compuverde
  • Crux Informatics
  • Data Inc.
  • Data Stax
  • Databricks
  • DataDirect Network
  • Dataiku
  • Datameer
  • Dell EMC
  • Deloitte
  • Domo
  • eClinicalWorks
  • Epic Systems Corporation
  • Facebook
  • Fluentd
  • Flytxt
  • Fujitsu
  • General Electric
  • GenomOncology
  • GoodData Corporation
  • Google
  • Greenplum
  • Gridgain Systems
  • Groundhog Technologies
  • Guavus
  • Hack/reduce
  • Hitachi Data Systems
  • Hortonworks
  • HP Enterprise
  • HPCC Systems
  • IBM
  • Illumina Inc
  • Imply Corporation
  • Informatica
  • Intel
  • Inter Systems Corporation
  • IVD Industry Connectivity Consortium
  • Jasper (Cisco)
  • Juniper Networks
  • Leica Biosystems (Danaher)
  • MapR
  • Marklogic
  • Mayo Medical Laboratories
  • McKesson Corporation
  • Medical Information Technology Inc.
  • Medopad
  • Microsoft
  • Microstrategy
  • MongoDB (Formerly 10Gen)
  • MU Sigma
  • Netapp
  • Netflix
  • NTT Data
  • Open Text (Actuate Corporation)
  • Oracle
  • Palantir Technologies Inc.
  • Pathway Genomics Corporation
  • Pentaho (Hitachi)
  • Perkin Elmer
  • Qlik Tech
  • Quality Systems Inc. (NextGen Healthcare)
  • Quantum
  • Quertle
  • Quest Diagnostics Inc.
  • Rackspace
  • Red Hat
  • Revolution Analytics
  • Roche Diagnostics
  • Rocket Fuel Inc. (Sizmek)
  • Salesforce
  • SAP
  • SAS Institute
  • ScienceSoft
  • Sense Networks
  • Shanghai Data Exchange
  • Sisense
  • Social Cops
  • Software AG/Terracotta
  • Sojern
  • Splice Machine
  • Splunk
  • Sumo Logic
  • Sunquest Information Systems
  • Supermicro
  • Tableau
  • Tableau Software
  • Tata Consultancy Services
  • Teradata
  • ThetaRay
  • Think Big Analytics
  • Thoughtworks
  • TIBCO
  • Tube Mogul (Adobe)
  • Uber
  • Verint Systems
  • VMware
  • VoloMetrix (Microsoft)
  • Wipro
  • Workday (Platfora)
  • WuXi NextCode Genomics (Genuity Science)
  • Zoomdata (Logi Analytics)

Table of Contents

1. Executive Summary

2. Big Data in Internet of Things

  • 2.1. Big Data in IoT Framework
  • 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
      • 2.2.3.1. Message Queuing Telemetry Transport
      • 2.2.3.2. Extensible Messaging and Presence Protocol
      • 2.2.3.3. Advanced Message Queuing Protocol
    • 2.2.4. Big Data in IoT Protocols for Network Interoperability
      • 2.2.4.1. Data Distribution Service
      • 2.2.4.2. Other IoT Protocols
    • 2.2.5. Big Data in IoT Data Processing Scalability
  • 2.3. Big Data in IoT Challenges
    • 2.3.1.1. Scalable High-volume Data Storage
    • 2.3.1.2. Data Management and Processing Raw Data in Multi-vendor Environment
    • 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 2022-2027
  • 5.3. Global Big Data Solutions in IoT Market 2022-2027
  • 5.4. Global Big Data in IoT Hardware, Software, and Services 2022-2027
  • 5.5. Global Big Data in IoT Products and Services 2022-2027
    • 5.5.1. Market for Big Data Collection in IoT 2022-2027
    • 5.5.2. Market for Big Data Storage in IoT 2022-2027
    • 5.5.3. Market for Big Data Analytics and Applications in IoT 2022-2027
    • 5.5.4. Markets for Big Data as a Service in IoT 2020 to 2028
  • 5.6. Big Data in IoT by Industry 2022-2027
    • 5.6.1. Big Data in IoT for Building Automation 2022-2027
    • 5.6.2. Big Data in IoT for Consumer Electronics 2022-2027
    • 5.6.3. Big Data in IoT for Financial Services 2022-2027
    • 5.6.4. Big Data in IoT for Government 2022-2027
    • 5.6.5. Big Data in IoT for Healthcare 2022-2027
    • 5.6.6. Big Data in IoT for Manufacturing 2022-2027
    • 5.6.7. Big Data in IoT for Oil and Gas 2020 to 2028
    • 5.6.8. Big Data in IoT for Retail Industry 2022-2027
    • 5.6.9. Big Data in IoT for ICT Industry 2022-2027
    • 5.6.10. Big Data in IoT for Transport and Cargo 2022-2027
    • 5.6.11. Big Data in IoT for Utilities Industry 2022-2027

6. Big Data Case Studies

  • 6.1. Organizations
    • 6.1.1. Climate Corporation
    • 6.1.2. Uber
    • 6.1.3. ScienceSoft
    • 6.1.4. CARTO
    • 6.1.5. Netflix
    • 6.1.6. Amazon
    • 6.1.7. Unique Identity Project
  • 6.2. Solution Approaches
    • 6.2.1. Security Intelligence
    • 6.2.2. Preventive Maintenance
    • 6.2.3. Retail Optimization

7. Select Company Analysis

  • 7.1. Key Developments by Major Players
  • 7.2. 1010Data (Advance Communication Corp.)
  • 7.3. Accenture
  • 7.4. Actian Corporation
  • 7.5. AdvancedMD
  • 7.6. Alation
  • 7.7. Allscripts Healthcare Solutions
  • 7.8. Alpine Data Labs
  • 7.9. Alteryx
  • 7.10. Amazon
  • 7.11. Apache Software Foundation
  • 7.12. Apple Inc.
  • 7.13. APTEAN (Formerly CDC Software)
  • 7.14. AthenaHealth Inc.
  • 7.15. Attunity
  • 7.16. Booz Allen Hamilton
  • 7.17. Bosch
  • 7.18. BGI
  • 7.19. Big Panda
  • 7.20. Capgemini
  • 7.21. Cerner Corporation
  • 7.22. Cisco Systems
  • 7.23. Cloudera
  • 7.24. Cogito Ltd.
  • 7.25. Compuverde
  • 7.26. Computer Science Corporation
  • 7.27. Crux Informatics
  • 7.28. DataDirect Network
  • 7.29. Data Inc.
  • 7.30. Databricks
  • 7.31. Dataiku
  • 7.32. Datameer
  • 7.33. Data Stax
  • 7.34. Dell EMC
  • 7.35. Deloitte
  • 7.36. Domo
  • 7.37. eClinicalWorks
  • 7.38. Epic Systems Corporation
  • 7.39. Facebook
  • 7.40. Fluentd
  • 7.41. Flytxt
  • 7.42. Fujitsu
  • 7.43. General Electric
  • 7.44. GenomOncology
  • 7.45. GoodData Corporation
  • 7.46. Google
  • 7.47. Greenplum
  • 7.48. Gridgain Systems
  • 7.49. Groundhog Technologies
  • 7.50. Guavus
  • 7.51. Hack/reduce
  • 7.52. HPCC Systems
  • 7.53. HP Enterprise
  • 7.54. Hitachi Data Systems
  • 7.55. Hortonworks
  • 7.56. IBM
  • 7.57. Illumina Inc
  • 7.58. Imply Corporation
  • 7.59. Informatica
  • 7.60. Inter Systems Corporation
  • 7.61. Intel
  • 7.62. IVD Industry Connectivity Consortium
  • 7.63. Jasper (Cisco)
  • 7.64. Juniper Networks
  • 7.65. Leica Biosystems (Danaher)
  • 7.66. MapR
  • 7.67. Marklogic
  • 7.68. Mayo Medical Laboratories
  • 7.69. McKesson Corporation
  • 7.70. Medical Information Technology Inc.
  • 7.71. Medopad
  • 7.72. Microsoft
  • 7.73. Microstrategy
  • 7.74. MongoDB (Formerly 10Gen)
  • 7.75. MU Sigma
  • 7.76. Netapp
  • 7.77. NTT Data
  • 7.78. Open Text (Actuate Corporation)
  • 7.79. Oracle
  • 7.80. Palantir Technologies Inc.
  • 7.81. Pathway Genomics Corporation
  • 7.82. Perkin Elmer
  • 7.83. Pentaho (Hitachi)
  • 7.84. Qlik Tech
  • 7.85. Quality Systems Inc. (NextGen Healthcare)
  • 7.86. Quantum
  • 7.87. Quertle
  • 7.88. Quest Diagnostics Inc.
  • 7.89. Rackspace
  • 7.90. Red Hat
  • 7.91. Revolution Analytics
  • 7.92. Roche Diagnostics
  • 7.93. Rocket Fuel Inc. (Sizmek)
  • 7.94. Salesforce
  • 7.95. SAP
  • 7.96. SAS Institute
  • 7.97. Sense Networks
  • 7.98. Shanghai Data Exchange
  • 7.99. Sisense
  • 7.100. Social Cops
  • 7.101. Software AG/Terracotta
  • 7.102. Sojern
  • 7.103. Splice Machine
  • 7.104. Splunk
  • 7.105. Sumo Logic
  • 7.106. Sunquest Information Systems
  • 7.107. Supermicro
  • 7.108. Tableau Software
  • 7.109. Tableau
  • 7.110. Tata Consultancy Services
  • 7.111. Teradata
  • 7.112. ThetaRay
  • 7.113. Thoughtworks
  • 7.114. Think Big Analytics
  • 7.115. TIBCO
  • 7.116. TubeMogul (Adobe)
  • 7.117. Verint Systems
  • 7.118. VolMetrix (Microsoft)
  • 7.119. VMware
  • 7.120. Wipro
  • 7.121. Workday (Platfora)
  • 7.122. WuXi NextCode Genomics (Genuity Science)
  • 7.123. Zoomdata (Logi Analytics)

8. Summary and Conclusions

  • 8.1. Emerging Opportunity Areas within Big Data in IoT
    • 8.1.1. IoT Data Management and Analytics Marketplace
      • 8.1.1.1. IoT Data as a Service
      • 8.1.1.2. IoT Data Analytics as a Service
    • 8.1.2. Decisions as a Service
  • 8.2. Evolution of Structured and Unstructured Data Exchange
    • 8.2.1. Phase One: Limited Data Exchange
    • 8.2.2. Phase Two: Selective Data Exchange between Industries
    • 8.2.3. Phase Three: Expanded Data Exchange across Industries and Between Competitors

Figures

  • Figure 1: Framework for Big Data in IoT
  • Figure 2: Big Data in IoT Care of Custody
  • Figure 3: Big Data in IoT Direct vs. Indirect Monetization
  • Figure 4: Big Data in IoT Internal vs. External Monetization
  • Figure 5: Big Data in IoT Hybrid Data from Merged Sources
  • Figure 6: New Revenue and Operational Benefits of Big Data in IoT
  • Figure 7: Big Data in Internet of Things 2022 - 2027
  • Figure 8: Big Data in IoT by Solution 2022 - 2027
  • Figure 9: Big Data in IoT Products and Services 2022 - 2027
  • Figure 10: Market for Big Data Collection in IoT 2022 - 2027
  • Figure 11: Regional Markets for Big Data Collection in IoT 2022 - 2027
  • Figure 12: Big Data Storage in IoT Market 2022 - 2027
  • Figure 13: Regional Market for Big Data Storage in IoT 2022 - 2027
  • Figure 14: Big Data Analytics and Applications in IoT Market 2022 - 2027
  • Figure 15: Regional Markets for Big Data Analytics and Applications in IoT 2022 - 2027
  • Figure 16: Big Data as a Service in IoT Market 2022 - 2027
  • Figure 17: Regional Markets for Big Data as a Service in IoT 2022 - 2027
  • Figure 18: Big Data in IoT by Industry Vertical 2022 - 2027
  • Figure 19: Big Data in IoT for Building Automation 2022 - 2027
  • Figure 20: Big Data in IoT for Consumer Electronics 2022 - 2027
  • Figure 21: Big Data in IoT for Financial Services 2022 - 2027
  • Figure 22: Big Data in IoT for Government 2022 - 2027
  • Figure 23: Big Data in IoT for Healthcare 2022 - 2027
  • Figure 24: Big Data in IoT for Manufacturing 2022 - 2027
  • Figure 25: Big Data in IoT for Oil & Gas 2022 - 2027
  • Figure 26: Big Data in IoT for Retail Industry 2022 - 2027
  • Figure 27: Big Data in IoT for ICT Industry 2022 - 2027
  • Figure 28: Big Data in IoT for Transport and Cargo 2022 - 2027
  • Figure 29: Big Data in IoT for Utilities 2022 - 2027
  • Figure 30: IoT Data Exchange Marketplace
  • Figure 31: Phase One is Limited IoT Data Sharing with no Formalized Mediation
  • Figure 32: Phase Two is IoT Data Sharing between Limited Industries
  • Figure 33: Phase Three is IoT Data across Industries and between Competitors

Tables

  • Table 1: Big Data in Internet of Things 2022 - 2027
  • Table 2: Market for Big Data in IoT by Solution Type 2022 - 2027
  • Table 3: Market for Big Data in IoT by Hardware, Software, and Services 2022 - 2027
  • Table 4: Big Data in IoT Products and Services 2022 - 2027
  • Table 5: Market for Big Data Collection in IoT 2022 - 2027
  • Table 6: Regional Markets for Big Data Collection in IoT 2022 - 2027
  • Table 7: Big Data Storage in IoT Market 2022 - 2027
  • Table 8: Regional Markets for Big Data Storage Infrastructure in IoT 2022 - 2027
  • Table 9: Big Data Analytics and Applications in IoT Market 2022 - 2027
  • Table 10: Regional Markets for Big Data Analytics and Applications in IoT 2022 - 2027
  • Table 11: Big Data as a Service in IoT Market 2022 - 2027
  • Table 12: Regional Markets for Big Data as a Service in IoT 2022 - 2027
  • Table 13: Big Data in IoT by Industry Vertical 2022 - 2027
  • Table 14: IoT Data Analytics Revenue by Solution and Services 2022 - 2027
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Jeroen Van Heghe

Manager - EMEA

+32-2-535-7543

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Christine Sirois

Manager - Americas

+1-860-674-8796

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