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市場調查報告書

巨量資料市場:各主要企業、解決方案、利用案例、商務案例、基礎設施、技術整合、產業、地區以及各國

Big Data Market by Leading Companies, Solutions, Use Cases, Business Cases, Infrastructure, Technology Integration, Industry Verticals, Region and Countries 2019 - 2024

出版商 Mind Commerce 商品編碼 434554
出版日期 內容資訊 英文 343 Pages
商品交期: 最快1-2個工作天內
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巨量資料市場:各主要企業、解決方案、利用案例、商務案例、基礎設施、技術整合、產業、地區以及各國 Big Data Market by Leading Companies, Solutions, Use Cases, Business Cases, Infrastructure, Technology Integration, Industry Verticals, Region and Countries 2019 - 2024
出版日期: 2019年03月11日內容資訊: 英文 343 Pages
簡介

本報告提供全球巨量資料市場相關調查分析,商務案例,應用的使用案例,業者情勢,價值鏈分析,案例研究等系統性資訊。

第1章 摘要整理

第2章 簡介

第3章 巨量資料的課題與機會

  • 巨量資料基礎設施的確保
  • 非結構化資料和IoT

第4章 巨量資料技術和商務案例

  • 巨量資料技術
  • 新興技術、工具、技巧
  • 巨量資料發展藍圖
  • 推動市場要素
  • 市場障礙

第5章 巨量資料的主要部門

  • 產業用網際網路和M2M
  • 零售和飯店
  • 媒體
  • 公共事業
  • 金融服務
  • 醫療保健、醫藥品
  • 通訊
  • 政府、國防安全保障
  • 其他

第6章 巨量資料的價值鏈

  • 巨量資料價值的片斷化
  • 資料收集、供應
  • 資料保管、商業智慧
  • 分析和視覺化
  • 動作、商務流程管理
  • 資料管治

第7章 巨量資料分析

  • 巨量資料分析所扮演的角色和重要性
  • 反應的 vs. 前瞻性分析
  • 技術、實行方法

第8章 標準化、規定上的課題

第9章 巨量資料的主要企業

  • 供應商評估矩陣

第10章 巨量資料市場分析與預測

  • 全球巨量資料市場
  • 巨量資料的各解決方案類型市場
  • 巨量資料的各地區市場

第11章 巨量資料市場產品市場區隔分析與預測

  • 各管理公共事業的巨量資料市場
  • 各功能市場區隔的巨量資料市場
  • 新興技術的巨量資料市場
  • 各產業類型的巨量資料市場
  • 各地區的巨量資料市場

第12章 附錄

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目錄

Overview:

The big data market consists of infrastructure providers, data centers, data as a service providers, and other vendors. Solutions for managing unstructured data are evolving beyond systems aligned towards primarily human-generated data (such as social networking, messaging, and browsing habits) towards increasingly greater emphasis upon machine-generated data found across many industry verticals.

For example, manufacturing and healthcare are anticipated to create massive amounts of data that may be rendered useful only through advanced analytics and various Artificial Intelligence (AI) technologies such as machine learning and cognitive computing. The long-term prospect for these technologies is that they will become embedded in many different other technologies and provide autonomous decision making on behalf of humans, both directly, and indirectly through many processes, products, and services.

Emerging networks and systems such as IoT and edge computing will generate substantial amounts of unstructured data, which will present both technical challenges and market opportunities for operating companies and their vendors. Emerging big data tools such as open APIs much be implemented to facilitate data capture and processing with the ability to perform localized processing and decision making.

Big data solution provider dynamics are evolving almost as much as the data management technologies themselves. While some companies rely upon proprietary solutions, many leading companies such as Hortonworks and Cloudera offer products and services primarily based on open source Apache Hadoop technology. One important distinction between market leaders is collaboration vs. competition. For example, Cloudera competes with IBM, Microsoft and others in data science and AI whereas Hortonworks partners with these companies.

In terms of data management and analytics technologies, the big data industry is experiencing profound changes across the entire stack including infrastructure, security, analytics, and the application layer. Mind Commerce sees the data services industry as whole shifting from host-based network topologies to cloud-based, data-centric architectures, thereby creating enormous challenges and opportunities for transitioning and securing data systems. In concert with this shift, big data infrastructure will require strategic governance and framework for optimized security.

Advanced analytics provide the ability to make raw data meaningful and useful as information for decision-making purposes. AI enhances the ability for 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.

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. However, real-time data is anticipated to become a highly valuable aspect of all solutions as a determinant of user behavior, application effectiveness, and identifier of new and enhanced mobile/wireless and/or IoT related apps and services.

Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) are perhaps best known as data intensive immersive technologies that require high bandwidth for operations. One of the least evaluated opportunities is the market opportunities associated with visualizing data and information in AR, VR, and MR environments. Much of this data will be unstructured, requiring big data analytics tools to process, categorize, and display in a meaningful manner. This will allow the end user to visualize and utilize information in ways previously inconceivable.

In addition, leading data management companies are developing tools for improved data visualization, facilitating improved information interpretation and decision making. Coupled with AI and cognitive computing, the field of advanced data visualization and analytics known as augmented analytics is transforming otherwise useless data into highly valuable and actionable smart data, often enabling dynamic decision making that may positively impact business operations as processes, transactions, and other events occur. Much of this smart data will monetized in a data as a service approach by enterprise thanks to leading big data service provider solutions.

‘Big Data Market by Leading Companies, Solutions, Use Cases, Business Cases, Infrastructure, Technology Integration, Industry Verticals, Regions and Countries 2019 - 2024’ provides an in-depth assessment of the global Big Data market, including business case issues/analysis, application use cases, vendor landscape, value chain analysis, and a quantitative assessment of the industry with forecasting from 2019 to 2024. This report also evaluates the components of Big Data infrastructure and security framework. Additional topics covered in this report include:

  • Big Data Technology: Analysis of infrastructure and important issues such as security and privacy
  • Big Data Use Cases: A review of investments sectors and specific use cases for the Big Data market
  • The Big Data Value Chain: An analysis of the value chain of Big Data and the major players involved within it
  • The Business Case for Big Data: An assessment of the business case, growth drivers and barriers for Big Data
  • Big Data Vendor Assessment: Assessment of the vendor landscape of leading players within the Big Data market
  • Market Analysis and Forecasts: Global and regional assessment of the market size and forecasts for 2019 to 2024

This report also includes analysis and forecasts for streaming data analytics. IoT facilitates vast amounts of fast-moving data from sensors and devices. For many use cases, data flows constantly from the device or sensor to the network and sometimes back to the device. In some cases, these streams of data are simply stored (for potential later use) and in other cases there is a need for real-time data processing and analytics. All direct purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Report Findings:

  • Big data in cognitive computing will reach $12.6B USD globally by 2024
  • Big data application infrastructure will reach $9.1B USD globally by 2024
  • Big data in public safety and homeland security will reach $5.3B USD globally by 2024
  • Real-time data will be a key value proposition for all use cases, segments, and solutions
  • Market leading companies are rapidly integrated big data technologies with IoT infrastructure

Report Benefits:

  • Detailed forecasts 2019 - 2024
  • Identify leading market segments
  • Learn about Big Data technologies
  • Identify key players and strategies
  • Understand market drivers and barriers
  • Identify opportunities in IoT data analytics
  • Understand regulatory issues and initiatives
  • Understand business case for enterprise Big Data

Target Audience:

  • IoT companies
  • Network service providers
  • Systems integration companies
  • Big Data and Analytics companies
  • Advertising and media companies
  • Enterprise across all industry verticals
  • Cloud and IoT product and service providers

Companies in Report:

  • 1010Data (Advance Communication Corp.)
  • Accenture
  • Actian Corporation
  • AdvancedMD
  • Alation
  • Allscripts Healthcare Solutions
  • Alpine Data Labs
  • Alteryx
  • Amazon
  • Anova Data
  • Apache Software Foundation
  • Apple Inc.
  • APTEAN (Formerly CDC Software)
  • Athena Health Inc.
  • Attunity
  • Booz Allen Hamilton
  • Bosch Software Innovations: Bosch IoT Suite
  • BGI
  • Big Panda
  • Bina Technologies Inc.
  • Capgemini
  • Cerner Corporation
  • Cisco Systems
  • CLC Bio
  • Cloudera
  • Cogito Ltd.
  • Compuverde
  • CRAY Inc.
  • Computer Science Corporation (CSC)
  • Crux Informatics
  • Ctrl Shift
  • Cvidya
  • Cybatar
  • DataDirect Network
  • Data Inc.
  • Databricks
  • Dataiku
  • Datameer
  • Data Stax
  • Definiens
  • Dell EMC
  • Deloitte
  • Domo
  • eClinicalWorks
  • Epic Systems Corporation
  • Facebook
  • Fluentd
  • Flytxt
  • Fujitsu
  • Genalice
  • General Electric
  • GenomOncology
  • GoodData Corporation
  • Google
  • Greenplum
  • Grid Gain Systems
  • Groundhog Technologies
  • Guavus
  • Hack/reduce
  • HPCC Systems
  • HP Enterprise
  • Hitachi Data Systems
  • Hortonworks
  • IBM
  • Illumina Inc
  • Imply Corporation
  • Informatica
  • Inter Systems Corporation
  • Intel
  • IVD Industry Connectivity Consortium-IICC
  • Jasper (Cisco Jasper)
  • Juniper Networks
  • Knome,Inc.
  • Leica Biosystems (Danaher)
  • Longview
  • MapR
  • Marklogic
  • Mayo Medical Laboratories
  • McKesson Corporation
  • Medical Information Technology Inc. (MEDITECH)
  • Medio
  • Medopad
  • Microsoft
  • Microstrategy
  • MongoDB (Formerly 10Gen)
  • MU Sigma
  • N-of-One
  • Netapp
  • NTT Data
  • Open Text (Actuate Corporation)
  • Opera Solutions
  • Oracle
  • Palantir Technologies Inc.
  • Pathway Genomics Corporation
  • Perkin Elmer
  • Pentaho (Hitachi)
  • Platfora
  • Qlik Tech
  • Quality Systems Inc (QSI)
  • Quantum
  • Quertle
  • Quest Diagnostics Inc.
  • Rackspace
  • Red Hat
  • Revolution Analytics
  • Roche Diagnostics
  • Rocket Fuel Inc.
  • Salesforce
  • SAP
  • SAS Institute
  • Selventa Inc.
  • Sense Networks
  • Shanghai Data Exchange
  • Sisense
  • Social Cops
  • Software AG/Terracotta
  • Sojern
  • Splice Machine
  • Splunk
  • Sqrrl
  • Sumo Logic
  • Sunquest Information Systems
  • Supermicro
  • Tableau Software
  • Tableau
  • Tata Consultancy Services
  • Teradata
  • ThetaRay
  • Thoughtworks
  • Think Big Analytics
  • TIBCO
  • Tube Mogul
  • Verint Systems
  • VolMetrix
  • VMware (Part of EMC)
  • Wipro
  • Workday (Platfora)
  • WuXi NextCode Genomics
  • Zoomdata

Table of Contents

1.0. EXECUTIVE SUMMARY

2.0. INTRODUCTION

  • 2.1. Big Data Overview
    • 2.1.1. Defining Big Data
    • 2.1.2. Big Data Ecosystem
    • 2.1.3. Key Characteristics of Big Data
      • 2.1.3.1. Volume
      • 2.1.3.2. Variety
      • 2.1.3.3. Velocity
      • 2.1.3.4. Variability
      • 2.1.3.5. Complexity
  • 2.2. Research Background
    • 2.2.1. Scope
    • 2.2.2. Coverage
    • 2.2.3. Company Focus

3.0. BIG DATA CHALLENGES AND OPPORTUNITIES

  • 3.1. Securing Big Data Infrastructure
    • 3.1.1. Big Data Infrastructure
    • 3.1.2. Infrastructure Challenges
    • 3.1.3. Big Data Infrastructure Opportunities
      • 3.1.3.1. Securing State Data
      • 3.1.3.2. Securing APIs
      • 3.1.3.3. Securing Applications
      • 3.1.3.4. Securing Data for Analysis
      • 3.1.3.5. Securing User Privileges
      • 3.1.3.6. Securing Enterprise Data
  • 3.2. Unstructured Data and the Internet of Things
    • 3.2.1. New Protocols, Platforms, Streaming and Parsing, Software and Analytical Tools
    • 3.2.2. Big Data in IoT will require Lightweight Data Interchange Format
    • 3.2.3. Big Data in IoT will use Lightweight Protocols
    • 3.2.4. Big Data in IoT will need Protocol for Network Interoperability
    • 3.2.5. Big Data in IoT Demands Data Processing on Appropriate Scale

4.0. BIG DATA TECHNOLOGIES AND BUSINESS CASES

  • 4.1. Big Data Technology
    • 4.1.1. Hadoop
      • 4.1.1.1. Other Apache Projects
    • 4.1.2. NoSQL
      • 4.1.2.1. Hbase
      • 4.1.2.2. Cassandra
      • 4.1.2.3. Mongo DB
      • 4.1.2.4. Riak
      • 4.1.2.5. CouchDB
    • 4.1.3. MPP Databases
    • 4.1.4. Others and Emerging Technologies
      • 4.1.4.1. Storm
      • 4.1.4.2. Drill
      • 4.1.4.3. Dremel
      • 4.1.4.4. SAP HANA
      • 4.1.4.5. Gremlin & Giraph
  • 4.2. Emerging Technologies,Tools, and Techniques
    • 4.2.1. Streaming Analytics
    • 4.2.2. Cloud Technology
    • 4.2.3. Google Search
    • 4.2.4. Customize Analytical Tools
    • 4.2.5. Internet Keywords
    • 4.2.6. Gamification
  • 4.3. Big Data Roadmap
  • 4.4. Market Drivers
    • 4.4.1. Data Volume & Variety
    • 4.4.2. Increasing Adoption of Big Data by Enterprises and Telecom
    • 4.4.3. Maturation of Big Data Software
    • 4.4.4. Continued Investments in Big Data by Web Giants
    • 4.4.5. Business Drivers
  • 4.5. Market Barriers
    • 4.5.1. Privacy and Security: The ‘Big' Barrier
    • 4.5.2. Workforce Re-skilling and Organizational Resistance
    • 4.5.3. Lack of Clear Big Data Strategies
    • 4.5.4. Technical Challenges: Scalability & Maintenance
    • 4.5.5. Big Data Development Expertise

5.0. KEY SECTORS FOR BIG DATA

  • 5.1. Industrial Internet and Machine-to-Machine
    • 5.1.1. Big Data in M2M
    • 5.1.2. Vertical Opportunities
  • 5.2. Retail and Hospitality
    • 5.2.1. Improving Accuracy of Forecasts and Stock Management
    • 5.2.2. Determining Buying Patterns
    • 5.2.3. Hospitality Use Cases
    • 5.2.4. Personalized Marketing
  • 5.3. Media
    • 5.3.1. Social Media
    • 5.3.2. Social Gaming Analytics
    • 5.3.3. Usage of Social Media Analytics by Other Verticals
    • 5.3.4. Internet Keyword Search
  • 5.4. Utilities
    • 5.4.1. Analysis of Operational Data
    • 5.4.2. Application Areas for the Future
  • 5.5. Financial Services
    • 5.5.1. Fraud Analysis, Mitigation & Risk Profiling
    • 5.5.2. Merchant-Funded Reward Programs
    • 5.5.3. Customer Segmentation
    • 5.5.4. Customer Retention & Personalized Product Offering
    • 5.5.5. Insurance Companies
  • 5.6. Healthcare and Pharmaceutical
    • 5.6.1. Drug Development
    • 5.6.2. Medical Data Analytics
    • 5.6.3. Case Study: Identifying Heartbeat Patterns
  • 5.7. Telecommunications
    • 5.7.1. Telco Analytics: Customer/Usage Profiling and Service Optimization
    • 5.7.2. Big Data Analytic Tools
    • 5.7.3. Speech Analytics
    • 5.7.4. New Products and Services
  • 5.8. Government and Homeland Security
    • 5.8.1. Big Data Research
    • 5.8.2. Statistical Analysis
    • 5.8.3. Language Translation
    • 5.8.4. Developing New Applications for the Public
    • 5.8.5. Tracking Crime
    • 5.8.6. Intelligence Gathering
    • 5.8.7. Fraud Detection and Revenue Generation
  • 5.9. Other Sectors
    • 5.9.1. Aviation
    • 5.9.2. Transportation and Logistics: Optimizing Fleet Usage
    • 5.9.3. Real-Time Processing of Sports Statistics
    • 5.9.4. Education
    • 5.9.5. Manufacturing

6.0. BIG DATA VALUE CHAIN

  • 6.1. Fragmentation in the Big Data Value
  • 6.2. Data Acquisitioning and Provisioning
  • 6.3. Data Warehousing and Business Intelligence
  • 6.4. Analytics and Visualization
  • 6.5. Actioning and Business Process Management
  • 6.6. Data Governance

7.0. BIG DATA ANALYTICS

  • 7.1. The Role and Importance of Big Data Analytics
  • 7.2. Big Data Analytics Processes
  • 7.3. Reactive vs. Proactive Analytics
  • 7.4. Technology and Implementation Approaches
    • 7.4.1. Grid Computing
    • 7.4.2. In-Database processing
    • 7.4.3. In-Memory Analytics
    • 7.4.4. Data Mining
    • 7.4.5. Predictive Analytics
    • 7.4.6. Natural Language Processing
    • 7.4.7. Text Analytics
    • 7.4.8. Visual Analytics
    • 7.4.9. Association Rule Learning
    • 7.4.10. Classification Tree Analysis
    • 7.4.11. Machine Learning
    • 7.4.12. Neural Networks
    • 7.4.13. Multilayer Perceptron (MLP)
    • 7.4.14. Radial Basis Functions
      • 7.4.14.1. Support Vector Machines
      • 7.4.14.2. Naïve Bayes
      • 7.4.14.3. K-nearest Neighbors
    • 7.4.15. Geospatial Predictive Modelling
    • 7.4.16. Regression Analysis
    • 7.4.17. Social Network Analysis

8.0. STANDARDIZATION AND REGULATORY ISSUES

  • 8.1. Cloud Standards Customer Council
  • 8.2. National Institute of Standards and Technology
  • 8.3. OASIS
  • 8.4. Open Data Foundation
  • 8.5. Open Data Center Alliance
  • 8.6. Cloud Security Alliance
  • 8.7. International Telecommunications Union
  • 8.8. International Organization for Standardization

9.0. KEY BIG DATA COMPANIES AND SOLUTIONS

  • 9.1. Vendor Assessment Matrix
  • 9.2. 1010Data (Advance Communication Corp.)
  • 9.3. Accenture
  • 9.4. Actian Corporation
  • 9.5. AdvancedMD
  • 9.6. Alation
  • 9.7. Allscripts Healthcare Solutions
  • 9.8. Alpine Data Labs
  • 9.9. Alteryx
  • 9.10. Amazon
  • 9.11. Anova Data
  • 9.12. Apache Software Foundation
  • 9.13. Apple Inc.
  • 9.14. APTEAN (Formerly CDC Software)
  • 9.15. Athena Health Inc.
  • 9.16. Attunity
  • 9.17. Booz Allen Hamilton
  • 9.18. Bosch Software Innovations: Bosch IoT Suite
  • 9.19. BGI
  • 9.20. Big Panda
  • 9.21. Bina Technologies Inc.
  • 9.22. Capgemini
  • 9.23. Cerner Corporation
  • 9.24. Cisco Systems
  • 9.25. CLC Bio
  • 9.26. Cloudera
  • 9.27. Cogito Ltd.
  • 9.28. Compuverde
  • 9.29. CRAY Inc.
  • 9.30. Computer Science Corporation (CSC)
  • 9.31. Crux Informatics
  • 9.32. Ctrl Shift
  • 9.33. Cvidya
  • 9.34. Cybatar
  • 9.35. DataDirect Network
  • 9.36. Data Inc.
  • 9.37. Databricks
  • 9.38. Dataiku
  • 9.39. Datameer
  • 9.40. Data Stax
  • 9.41. Definiens
  • 9.42. Dell EMC
  • 9.43. Deloitte
  • 9.44. Domo
  • 9.45. eClinicalWorks
  • 9.46. Epic Systems Corporation
  • 9.47. Facebook
  • 9.48. Fluentd
  • 9.49. Flytxt
  • 9.50. Fujitsu
  • 9.51. Genalice
  • 9.52. General Electric
  • 9.53. GenomOncology
  • 9.54. GoodData Corporation
  • 9.55. Google
  • 9.56. Greenplum
  • 9.57. Grid Gain Systems
  • 9.58. Groundhog Technologies
  • 9.59. Guavus
  • 9.60. Hack/reduce
  • 9.61. HPCC Systems
  • 9.62. HP Enterprise
  • 9.63. Hitachi Data Systems
  • 9.64. Hortonworks
  • 9.65. IBM
  • 9.66. Illumina Inc
  • 9.67. Imply Corporation
  • 9.68. Informatica
  • 9.69. Inter Systems Corporation
  • 9.70. Intel
  • 9.71. IVD Industry Connectivity Consortium-IICC
  • 9.72. Jasper (Cisco Jasper)
  • 9.73. Juniper Networks
  • 9.74. Knome,Inc.
  • 9.75. Leica Biosystems (Danaher)
  • 9.76. Longview
  • 9.77. MapR
  • 9.78. Marklogic
  • 9.79. Mayo Medical Laboratories
  • 9.80. McKesson Corporation
  • 9.81. Medical Information Technology Inc. (MEDITECH)
  • 9.82. Medio
  • 9.83. Medopad
  • 9.84. Microsoft
  • 9.85. Microstrategy
  • 9.86. MongoDB (Formerly 10Gen)
  • 9.87. MU Sigma
  • 9.88. N-of-One
  • 9.89. Netapp
  • 9.90. NTT Data
  • 9.91. Open Text (Actuate Corporation)
  • 9.92. Opera Solutions
  • 9.93. Oracle
  • 9.94. Palantir Technologies Inc.
  • 9.95. Pathway Genomics Corporation
  • 9.96. Perkin Elmer
  • 9.97. Pentaho (Hitachi)
  • 9.98. Platfora
  • 9.99. Qlik Tech
  • 9.100. Quality Systems Inc (QSI)
  • 9.101. Quantum
  • 9.102. Quertle
  • 9.103. Quest Diagnostics Inc.
  • 9.104. Rackspace
  • 9.105. Red Hat
  • 9.106. Revolution Analytics
  • 9.107. Roche Diagnostics
  • 9.108. Rocket Fuel Inc.
  • 9.109. Salesforce
  • 9.110. SAP
  • 9.111. SAS Institute
  • 9.112. Selventa Inc.
  • 9.113. Sense Networks
  • 9.114. Shanghai Data Exchange
  • 9.115. Sisense
  • 9.116. Social Cops
  • 9.117. Software AG/Terracotta
  • 9.118. Sojern
  • 9.119. Splice Machine
  • 9.120. Splunk
  • 9.121. Sqrrl
  • 9.122. Sumo Logic
  • 9.123. Sunquest Information Systems
  • 9.124. Supermicro
  • 9.125. Tableau Software
  • 9.126. Tableau
  • 9.127. Tata Consultancy Services
  • 9.128. Teradata
  • 9.129. ThetaRay
  • 9.130. Thoughtworks
  • 9.131. Think Big Analytics
  • 9.132. TIBCO
  • 9.133. Tube Mogul
  • 9.134. Verint Systems
  • 9.135. VolMetrix
  • 9.136. VMware (Part of EMC)
  • 9.137. Wipro
  • 9.138. Workday (Platfora)
  • 9.139. WuXi NextCode Genomics
  • 9.140. Zoomdata

10.0. OVERALL BIG DATA MARKET ANALYSIS AND FORECASTS 2019-2024

  • 10.1. Global Big Data Marketplace
  • 10.2. Big Data Market by Solution Type
  • 10.3. Regional Big Data Market

11.0. BIG DATA MARKET SEGMENT ANALYSIS AND FORECASTS 2019-2024

  • 11.1. Big Data Market by Management Utilities 2019-2024
    • 11.1.1. Market for Servers and Other Hardware
    • 11.1.2. Market for Big Data Application Infrastructure and Middleware
    • 11.1.3. Market for Data Integration Tools & Data Quality Tools
    • 11.1.4. Big Data Market for Database Management Systems
    • 11.1.5. Big Data Market for Storage Management
  • 11.2. Big Data Market by Functional Segment 2019-2024
    • 11.2.1. Big Data in Supply Chain Management
    • 11.2.2. Big Data in Workforce Analytics
    • 11.2.3. Big Data in Enterprise Performance Analytics
    • 11.2.4. Big Data in Professional Services
    • 11.2.5. Big Data in Business Intelligence
    • 11.2.6. Big Data in Social Media & Content Analytics
  • 11.3. Market for Big Data in Emerging Technologies 2019-2024
    • 11.3.1. Big Data in Internet of Things
    • 11.3.2. Big Data in Smart Cities
    • 11.3.3. Big Data in Blockchain and Cryptocurrency
    • 11.3.4. Big Data in Augmented and Virtual Reality
    • 11.3.5. Big Data in Cybersecurity
    • 11.3.6. Big Data in Smart Assistants
    • 11.3.7. Big Data in Cognitive Computing
    • 11.3.8. Big Data in CRM
    • 11.3.9. Big Data in Spatial Information
  • 11.4. Big Data Market by Industry Type 2019-2024
  • 11.5. Regional Big Data Markets 2019-2024
    • 11.5.1. North America Market for Big Data
    • 11.5.2. South American Market for Big Data
    • 11.5.3. Western European Market for Big Data
    • 11.5.4. Central and Eastern European Market for Big Data
    • 11.5.5. APAC Market for Big Data
    • 11.5.6. MEA Market for Big Data

12.0. APPENDIX: BIG DATA SUPPORT OF STREAMING IOT DATA

  • 12.1. Big Data Technology Market Outlook for Streaming IoT Data
    • 12.1.1. IoT Data Management is a Ubiquitous Opportunity across Enterprise
    • 12.1.2. IoT Data becomes a Big Data Revenue Opportunity
    • 12.1.3. Real-time Streaming IoT Data Analytics is a Substantial Opportunity
  • 12.2. Global Streaming IoT Data Analytics Revenue
    • 12.2.1. Overall Streaming Data Analytics Revenue for IoT
    • 12.2.2. Global Streaming IoT Data Analytics Revenue by App, Software, and Services
    • 12.2.3. Global Streaming IoT Data Analytics Revenue in Industry Verticals
      • 12.2.3.1. Streaming IoT Data Analytics Revenue in Retail
        • 12.2.3.1.1. Streaming IoT Data Analytics Revenue by Retail Segment
        • 12.2.3.1.2. Streaming IoT Data Analytics Retail Revenue by App, Software, and Service
      • 12.2.3.2. Streaming IoT Data Analytics Revenue in Telecom and IT
        • 12.2.3.2.1. Streaming IoT Data Analytics Revenue by Telecom and IT Segment
        • 12.2.3.2.2. Streaming IoT Data Analytics Revenue by Telecom & IT App, Software, and Service
      • 12.2.3.3. Streaming IoT Data Analytics Revenue in Energy and Utility
        • 12.2.3.3.1. Streaming IoT Data Analytics Revenue by Energy and Utility Segment
        • 12.2.3.3.2. Streaming IoT Data Analytics Energy and Utilities Revenue by App, Software, and Service
      • 12.2.3.4. Streaming IoT Data Analytics Revenue in Government
        • 12.2.3.4.1. Streaming IoT Data Analytics Revenue by Government Segment
        • 12.2.3.4.2. Streaming IoT Data Analytics Government Revenue by App, Software, and Service
      • 12.2.3.5. Streaming IoT Data Analytics Revenue in Healthcare and Life Science
        • 12.2.3.5.1. Streaming IoT Data Analytics Revenue by Healthcare Segment
      • 12.2.3.6. Streaming IoT Data Analytics Revenue in Manufacturing
        • 12.2.3.6.1. Streaming IoT Data Analytics Revenue by Manufacturing Segment
        • 12.2.3.6.2. Streaming IoT Data Analytics Manufacturing Revenue by App, Software, and Service
      • 12.2.3.7. Streaming IoT Data Analytics Revenue in Transportation & Logistics
        • 12.2.3.7.1. Streaming IoT Data Analytics Revenue by Transportation & Logistics Segment
        • 12.2.3.7.2. Streaming IoT Data Analytics Transportation & Logistics Revenue by App, Software, and Service
      • 12.2.3.8. Streaming IoT Data Analytics Revenue in Banking and Finance
        • 12.2.3.8.1. Streaming IoT Data Analytics Revenue by Banking and Finance Segment
        • 12.2.3.8.2. Streaming IoT Data Analytics Revenue by Banking & Finance App, Software, and Service
      • 12.2.3.9. Streaming IoT Data Analytics Revenue in Smart Cities
        • 12.2.3.9.1. Streaming IoT Data Analytics Revenue by Smart City Segment
      • 12.2.3.10. Streaming IoT Data Analytics Revenue in Automotive
        • 12.2.3.10.1. Streaming IoT Data Analytics Revenue by Automobile Industry Segment
        • 12.2.3.10.2. Streaming IoT Data Analytics Revenue by Automotive Industry App, Software, and Service
      • 12.2.3.11. Streaming IoT Data Analytics Revenue in Education
        • 12.2.3.11.1. Streaming IoT Data Analytics Revenue by Education Industry Segment
        • 12.2.3.11.2. Streaming IoT Data Analytics Revenue by Education Industry App, Software, and Service
      • 12.2.3.12. Streaming IoT Data Analytics Revenue in Outsourcing Services
        • 12.2.3.12.1. Streaming IoT Data Analytics Revenue by Outsourcing Segment
        • 12.2.3.12.2. Streaming IoT Data Analytics Revenue by Outsourcing Industry App, Software, and Service
      • 12.2.3.13. Streaming IoT Data Analytics Revenue by Leading Vendor Platform
  • 12.3. Regional Streaming IoT Data Analytics Revenue
    • 12.3.1. Revenue in Region
    • 12.3.2. APAC Market Revenue
    • 12.3.3. Europe Market Revenue
    • 12.3.4. North America Market Revenue
    • 12.3.5. Latin America Market Revenue
    • 12.3.6. ME&A Market Revenue
  • 12.4. Streaming IoT Data Analytics Revenue by Country
    • 12.4.1. Revenue by APAC Countries
      • 12.4.1.1. Leading Countries
      • 12.4.1.2. Japan Market Revenue
      • 12.4.1.3. China Market Revenue
      • 12.4.1.4. India Market Revenue
      • 12.4.1.5. Australia Market Revenue
    • 12.4.2. Revenue by Europe Countries
      • 12.4.2.1. Leading Countries
      • 12.4.2.2. Germany Market Revenue
      • 12.4.2.3. UK Market Revenue
      • 12.4.2.4. France Market Revenue
    • 12.4.3. Revenue by North America Countries
      • 12.4.3.1. Leading Countries
      • 12.4.3.2. US Market Revenue
      • 12.4.3.3. Canada Market Revenue
    • 12.4.4. Revenue by Latin America Countries
      • 12.4.4.1. Leading Countries
      • 12.4.4.2. Brazil Market Revenue
      • 12.4.4.3. Mexico Market Revenue
    • 12.4.5. Revenue by ME&A Countries
      • 12.4.5.1. Leading Countries
      • 12.4.5.2. South Africa Market Revenue
      • 12.4.5.3. UAE Market Revenue

Figures

  • Figure 1: Big Data Ecosystem
  • Figure 2: Key Characteristics of Big Data
  • Figure 3: Big Data Use Cases in Industry Verticals
  • Figure 4: Big Data Stack
  • Figure 5: Framework for Big Data in IoT
  • Figure 6: NoSQL vs Legacy DB Performance Comparisons
  • Figure 7: Roadmap Big Data Technologies 2018 - 2030
  • Figure 8: The Big Data Value Chain
  • Figure 9: Big Data Value Flow
  • Figure 10: Big Data Analytics
  • Figure 11: Big Data Vendor Ranking Matrix
  • Figure 12: Global Big Data Market
  • Figure 13: Big Data Market by Solution Type
  • Figure 14: Regional Market for Big Data
  • Figure 15: Big Data Market by Management Utilities
  • Figure 16: Market for Servers and Other Hardware
  • Figure 17: Market for Application Infrastructure & Middleware
  • Figure 18: Big Data Market for Data Integration Tools & Data Quality Tools
  • Figure 19: Market for Database Management Systems
  • Figure 20: Market for Storage Management
  • Figure 21: Big Data Market by Functional Segment
  • Figure 22: Big Data in Supply Chain Management
  • Figure 23: Big Data in Workforce Analytics
  • Figure 24: Big Data in Enterprise Performance Analytics
  • Figure 25: Big Data in Professional Services
  • Figure 26: Big Data in Business Intelligence
  • Figure 27: Big Data in Social Media & Content Analytics
  • Figure 28: Market for Big Data in Emerging Technologies
  • Figure 29: Big Data in Internet of Things
  • Figure 30: Big Data in Smart Cities
  • Figure 31: Big Data in Blockchain and Cryptocurrency
  • Figure 32: Big Data in Augmented and Virtual Reality
  • Figure 33: Big Data in Cybersecurity
  • Figure 34: Big Data in Smart Assistants
  • Figure 35: Big Data in Cognitive Computing
  • Figure 36: Big Data in CRM
  • Figure 37: Big Data in Spatial Information
  • Figure 38: Big Data Market by Industry Type
  • Figure 39: Big Data Applications in Transportation
  • Figure 40: Big Data Applications in Automobiles
  • Figure 41: North America Big Data Market by Solution Type
  • Figure 42: North America Big Data Market by Management Utilities
  • Figure 43: North America Big Data Market by Functional Segments
  • Figure 44: North America Market for Big Data in Emerging Technologies
  • Figure 45: North America Big Data Market by Industry Type
  • Figure 46: South America Big Data Market by Solution Type
  • Figure 47: South America Big Data Market by Management Utilities
  • Figure 48: South America Big Data Market by Functional Segments
  • Figure 49: South America Market for Big Data in Emerging Technologies
  • Figure 50: South America Big Data Market by Industry Type
  • Figure 51: Western Europe Big Data Market by Solution Type
  • Figure 52: Western Europe Big Data Market by Management Utilities
  • Figure 53: Western Europe Big Data Market by Functional Segments
  • Figure 54: Western Europe Market for Big Data in Emerging Technologies
  • Figure 55: Western Europe Big Data Market by Industry Type
  • Figure 56: Central and Eastern Europe Big Data Market by Solution Type
  • Figure 57: Central and Eastern Europe Big Data Market by Management Utilities
  • Figure 58: Central and Eastern Europe Big Data Market by Functional Segments
  • Figure 59: Central and Eastern Europe Market for Big Data in Emerging Tech
  • Figure 60: Central and Eastern Europe Big Data Market by Industry Type
  • Figure 61: APAC Big Data Market by Solution Type
  • Figure 62: APAC Big Data Market by Management Utilities
  • Figure 63: APAC Big Data Market by Functional Segment
  • Figure 64: APAC Market for Big Data in Emerging Technologies
  • Figure 65: APAC Big Data Market by Industry Type
  • Figure 66: MEA Big Data Market by Solution Type
  • Figure 67: MEA Big Data Market by Management Utilities
  • Figure 68: MEA Big Data Market by Functional Segments
  • Figure 69: MEA Market for Big Data in Emerging Technologies
  • Figure 70: MEA Big Data Market by Industry Type
  • Figure 71: Streaming IoT Data Sources Compared
  • Figure 72: Overall Streaming IoT Data Analytics

Tables

  • Table 1: Global Markets for Big Data
  • Table 2: Big Data Markets by the Type of Plan
  • Table 3: Regional Markets for Big Data
  • Table 4: Big Data Market by Management Utilities
  • Table 5: Market for Servers and Other Hardware
  • Table 6: Big Data Market for Application Infrastructure & Middleware
  • Table 7: Market for Data Integration Tools & Data Quality Tools
  • Table 8: Market for Database Management Systems
  • Table 9: Market for Storage Management
  • Table 10: Big Data Market by Functional Segment
  • Table 11: Big Data in Supply Chain Management
  • Table 12: Big Data in Workforce Analytics
  • Table 13: Big Data in Enterprise Performance Analytics
  • Table 14: Big Data in Professional Services
  • Table 15: Big Data in Business Intelligence
  • Table 16: Big Data in Social Media & Content Analytics
  • Table 17: Market for Big Data in Emerging Technologies
  • Table 18: Big Data in Internet of Things
  • Table 19: Big Data in Smart Cities
  • Table 20: Big Data in Blockchain and Cryptocurrency
  • Table 21: Big Data in Augmented and Virtual Reality
  • Table 22: Big Data in Cybersecurity
  • Table 23: Big Data in Smart Assistants
  • Table 24: Big Data in Cognitive Computing
  • Table 25: Big Data in CRM
  • Table 26: Big Data in Spatial Information
  • Table 27: Big Data Market by Industry Type
  • Table 28: Big Data Applications in Transportation Market
  • Table 29: Big Data Applications in Automobiles
  • Table 28: North America Big Data Market by Solution Type
  • Table 29: North America Big Data Market by Management Utilities
  • Table 30: North America Big Data Market by Functional Segments
  • Table 31: North America Market for Big Data in Emerging Technologies
  • Table 32: North America Big Data Market by Industry Type
  • Table 33: South America Big Data Market by Solution Type
  • Table 34: South America: Big Data Market by Management Utilities
  • Table 35: South America Big Data Market by Functional Segments
  • Table 36: South America Market for Big Data in Emerging Technologies
  • Table 37: South America Big Data Market by Industry Type
  • Table 38: Western Europe Big Data Market by Solution Type
  • Table 39: Western Europe Big Data Market by Management Utilities
  • Table 40: Western Europe Big Data Market by Functional Segments
  • Table 41: Western Europe Market for Big Data in Emerging Technologies
  • Table 42: Western Europe Big Data Market by Industry Type
  • Table 43: Central and Eastern Europe Big Data Market by Solution Type
  • Table 44: Central and Eastern Europe Big Data Market by Management Utilities
  • Table 45: Central and Eastern Europe Big Data Market by Functional Segments
  • Table 46: Central and Eastern Europe Market for Big Data in Emerging Tech
  • Table 47: Central and Eastern Europe Big Data Market by Industry Type
  • Table 48: APAC Big Data Market by Solution Type
  • Table 49: APAC Big Data Market by Management Utilities
  • Table 50: APAC Big Data Market by Functional Segments
  • Table 51: APAC Market for Big Data in Emerging Technologies
  • Table 52: APAC Big Data Market by Industry Type
  • Table 53: MEA Big Data Market by Solution Type
  • Table 54: MEA Big Data Market by Management Utilities
  • Table 55: MEA Big Data Market by Functional Segments
  • Table 56: MEA Market for Big Data in Emerging Technologies
  • Table 57: MEA Big Data Market by Industry Type
  • Table 60: Global Streaming IoT Data Analytics Revenue by App, Software, and Service
  • Table 61: Global Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 62: Retail Streaming IoT Data Analytics Revenue by Retail Segment
  • Table 63: Retail Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 64: Telecom & IT Streaming IoT Data Analytics Rev by Segment
  • Table 65: Telecom & IT Streaming IoT Data Analytics Rev by App, Software, and Services
  • Table 66: Energy & Utilities Streaming IoT Data Analytics Rev by Segment
  • Table 67: Energy & Utilities Streaming IoT Data Analytics Rev by App, Software, and Services
  • Table 68: Government Streaming IoT Data Analytics Revenue by Segment
  • Table 19: Government Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 70: Healthcare & Life Science Streaming IoT Data Analytics Revenue by Segment
  • Table 71: Healthcare & Life Science Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 72: Manufacturing Streaming IoT Data Analytics Revenue by Segment
  • Table 73: Manufacturing Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 74: Transportation & Logistics Streaming IoT Data Analytics Revenue by Segment
  • Table 75: Transportation & Logistics Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 76: Banking and Finance Streaming IoT Data Analytics Revenue by Segment
  • Table 77: Banking & Finance Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 78: Smart Cities Streaming IoT Data Analytics Revenue by Segment
  • Table 79: Smart Cities Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 80: Automotive Streaming IoT Data Analytics Revenue by Segment
  • Table 81: Automotive Streaming IoT Data Analytics Revenue by Apps, Software, and Services
  • Table 82: Education Streaming IoT Data Analytics Revenue by Segment
  • Table 83: Education Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 84: Outsourcing Service Streaming IoT Data Analytics Revenue by Segment
  • Table 85: Outsourcing Service Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 86: Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 87: Streaming IoT Data Analytics Revenue in Region
  • Table 88: APAC Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 89: APAC Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 90: APAC Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 91: Europe Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 92: Europe Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 93: Europe Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 94: North America Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 95: North America Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 96: North America Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 97: Latin America Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 98: Latin America Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 99: Latin America Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 100: ME&A Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 101: ME&A Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 102: ME&A Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 103: Streaming IoT Data Analytics Revenue by APAC Countries
  • Table 54: Japan Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 105: Japan Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 106: China Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 107: China Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 108: India Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 109: India Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 110: Australia Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 111: Australia Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 112: Streaming IoT Data Analytics Revenue by Europe Countries
  • Table 113: Germany Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 114: Germany Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 115: UK Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 116: UK Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 117: France Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 118: France Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 119: Streaming IoT Data Analytics Revenue by North America Countries
  • Table 120: US Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 121: US Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 122: Canada Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 123: Canada Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 124: Streaming IoT Data Analytics Revenue by Latin America Countries
  • Table 75: Brazil Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 126: Brazil Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 127: Mexico Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 128: Mexico Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 129: Streaming IoT Data Analytics Revenue by ME&A Countries
  • Table 130: South Africa Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 131: South Africa Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 132: UAE Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 133: UAE Streaming IoT Data Analytics Revenue in Industry Vertical
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