Global Big Data in E-Commerce Market

Big Data in E-Commerce Comprehensive Study by Application (Inventory, Supply Chain, Forecasting, Pricing Strategies, Sales, Others), Components (Hardware, Software), Deployment (Cloud-Based (Private Cloud, Public Cloud), On-premises), Solution (Customer Analytics, Content Analytics, Risk Management, Fraud Detection, Others) Players and Region - Global Market Outlook to 2026

Big Data in E-Commerce Market by XX Submarkets | Forecast Years 2022-2027  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
What is Big Data in E-Commerce?
The big data in e-commerce contains a large collection of information that organizations can use to determine which products, prices, and advertising are appropriate to maximize the profits. As big data in e-commerce helps in providing the trends and helps e-commerce companies stay ahead with trends. It helps in predicting the latest trends to help retailers to know the product demand and customer preferences and what can be the next product in the market which helps them to stay ahead of their competitors.

The market study is broken down, by Application (Inventory, Supply Chain, Forecasting, Pricing Strategies, Sales and Others) and major geographies with country level break-up.

Established and emerging Players should take a closer view at their existing organizations and reinvent traditional business and operating models to adapt to the future.

Amazon Web Services (United States), Cloudera, Inc. (United States), Hewlett Packard Enterprise Company (United States), Hitachi, Ltd. (Japan), IBM (United States), Microsoft Corporation (United States), Oracle Corporation (United States), Palantir Technologies (United States), SAP SE (Germany), Splunk Inc. (United States), SAS Institute (United States) and Teradata Corporation (United States) are some of the key players that are part of study coverage.

Segmentation Overview
AdvanceMarketAnalytics has segmented the market of Global Big Data in E-Commerce market by Type, Application and Region.

On the basis of geography, the market of Big Data in E-Commerce has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Taiwan, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico). If we see Market by Components, the sub-segment i.e. Hardware will boost the Big Data in E-Commerce market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by Deployment, the sub-segment i.e. Cloud-Based (Private Cloud, Public Cloud) will boost the Big Data in E-Commerce market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by Solution, the sub-segment i.e. Customer Analytics will boost the Big Data in E-Commerce market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth.


"The U.S. Federal Trade Commission is extending its regulatory reach to the e-commerce impact of big data. The commission will not hesitate to enforce FTC Act prohibitions against unfair and deceptive practices related to big data in all applications, not just those affecting a particular segment of the population, it said in the report. It will utilize the same legal basis for big data situations that it uses for cases involving the hacking of consumer records, identity theft, and fraudulent misrepresentations in e-commerce transactions. That legal leverage "is not confined to particular market sectors but is generally applicable to most companies acting in commerce."

Market Trend
  • The Increasing Use of Big Data in E-Commerce to Predict the Latest Trends
  • Adoption of Artificial Intelligence in Big Data in E-Commerce

Market Drivers
  • The Growing E-Commerce Market Worldwide
  • Increasing Customer Base is Increasing the Demand for Better Operational Decisions, Strategic Decisions, and Other Major Decisions

Opportunities
  • Technological Advancements in E-Commerce
  • Data-Driven Programmatic Advertising for Identifying the Target Customers

Restraints
  • Privacy Related Issues with Big Data in E-Commerce

Challenges
  • Regulatory Compliances with Big Data in E-Commerce


Key Target Audience
Big Data in E-Commerce Owners, E-Commerce Industry Associations, Research and Development Institutes, Potential Investors, Regulatory Bodies and Others

About Approach
To evaluate and validate the market size various sources including primary and secondary analysis is utilized. AMA Research follows regulatory standards such as NAICS/SIC/ICB/TRCB, to have the better understanding of the market. The market study is conducted on basis of more than 200 companies dealing in the market regional as well as global areas with purpose to understand company’s positioning regarding market value, volume and their market share for regional as well as global.

Further to bring relevance specific to any niche market we set and apply number of criteria like Geographic Footprints, Regional Segments of Revenue, Operational Centres, etc. The next step is to finalize a team (In-House + Data Agencies) who then starts collecting C & D level executives and profiles, Industry experts, Opinion leaders etc. and work towards appointment generation.

The primary research is performed by taking the interviews of executives of various companies dealing in the market as well as using the survey reports, research institute, and latest research reports. Meanwhile, analyst team keeps preparing set of questionnaires and after getting appointee list; the target audience are then tapped and segregated with various mediums and channels that are feasible for making connection that includes email communication, telephonic, skype, LinkedIn Group & InMail, Community Forums, Community Forums, open Survey, SurveyMonkey etc.

Report Objectives / Segmentation Covered

By Application
  • Inventory
  • Supply Chain
  • Forecasting
  • Pricing Strategies
  • Sales
  • Others
By Components
  • Hardware
  • Software

By Deployment
  • Cloud-Based (Private Cloud, Public Cloud)
  • On-premises

By Solution
  • Customer Analytics
  • Content Analytics
  • Risk Management
  • Fraud Detection
  • Others

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. The Growing E-Commerce Market Worldwide
      • 3.2.2. Increasing Customer Base is Increasing the Demand for Better Operational Decisions, Strategic Decisions, and Other Major Decisions
    • 3.3. Market Challenges
      • 3.3.1. Regulatory Compliances with Big Data in E-Commerce
    • 3.4. Market Trends
      • 3.4.1. The Increasing Use of Big Data in E-Commerce to Predict the Latest Trends
      • 3.4.2. Adoption of Artificial Intelligence in Big Data in E-Commerce
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Big Data in E-Commerce, by Application, Components, Deployment, Solution and Region (value) (2015-2020)
    • 5.1. Introduction
    • 5.2. Global Big Data in E-Commerce (Value)
      • 5.2.1. Global Big Data in E-Commerce by: Application (Value)
        • 5.2.1.1. Inventory
        • 5.2.1.2. Supply Chain
        • 5.2.1.3. Forecasting
        • 5.2.1.4. Pricing Strategies
        • 5.2.1.5. Sales
        • 5.2.1.6. Others
      • 5.2.2. Global Big Data in E-Commerce by: Components (Value)
        • 5.2.2.1. Hardware
        • 5.2.2.2. Software
      • 5.2.3. Global Big Data in E-Commerce by: Deployment (Value)
        • 5.2.3.1. Cloud-Based (Private Cloud, Public Cloud)
        • 5.2.3.2. On-premises
      • 5.2.4. Global Big Data in E-Commerce by: Solution (Value)
        • 5.2.4.1. Customer Analytics
        • 5.2.4.2. Content Analytics
        • 5.2.4.3. Risk Management
        • 5.2.4.4. Fraud Detection
        • 5.2.4.5. Others
      • 5.2.5. Global Big Data in E-Commerce Region
        • 5.2.5.1. South America
          • 5.2.5.1.1. Brazil
          • 5.2.5.1.2. Argentina
          • 5.2.5.1.3. Rest of South America
        • 5.2.5.2. Asia Pacific
          • 5.2.5.2.1. China
          • 5.2.5.2.2. Japan
          • 5.2.5.2.3. India
          • 5.2.5.2.4. South Korea
          • 5.2.5.2.5. Taiwan
          • 5.2.5.2.6. Australia
          • 5.2.5.2.7. Rest of Asia-Pacific
        • 5.2.5.3. Europe
          • 5.2.5.3.1. Germany
          • 5.2.5.3.2. France
          • 5.2.5.3.3. Italy
          • 5.2.5.3.4. United Kingdom
          • 5.2.5.3.5. Netherlands
          • 5.2.5.3.6. Rest of Europe
        • 5.2.5.4. MEA
          • 5.2.5.4.1. Middle East
          • 5.2.5.4.2. Africa
        • 5.2.5.5. North America
          • 5.2.5.5.1. United States
          • 5.2.5.5.2. Canada
          • 5.2.5.5.3. Mexico
  • 6. Big Data in E-Commerce: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2020)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Amazon Web Services (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. Cloudera, Inc. (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. Hewlett Packard Enterprise Company (United States)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. Hitachi, Ltd. (Japan)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. IBM (United States)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. Microsoft Corporation (United States)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Oracle Corporation (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Palantir Technologies (United States)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. SAP SE (Germany)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Splunk Inc. (United States)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
      • 6.4.11. SAS Institute (United States)
        • 6.4.11.1. Business Overview
        • 6.4.11.2. Products/Services Offerings
        • 6.4.11.3. Financial Analysis
        • 6.4.11.4. SWOT Analysis
      • 6.4.12. Teradata Corporation (United States)
        • 6.4.12.1. Business Overview
        • 6.4.12.2. Products/Services Offerings
        • 6.4.12.3. Financial Analysis
        • 6.4.12.4. SWOT Analysis
  • 7. Global Big Data in E-Commerce Sale, by Application, Components, Deployment, Solution and Region (value) (2021-2026)
    • 7.1. Introduction
    • 7.2. Global Big Data in E-Commerce (Value)
      • 7.2.1. Global Big Data in E-Commerce by: Application (Value)
        • 7.2.1.1. Inventory
        • 7.2.1.2. Supply Chain
        • 7.2.1.3. Forecasting
        • 7.2.1.4. Pricing Strategies
        • 7.2.1.5. Sales
        • 7.2.1.6. Others
      • 7.2.2. Global Big Data in E-Commerce by: Components (Value)
        • 7.2.2.1. Hardware
        • 7.2.2.2. Software
      • 7.2.3. Global Big Data in E-Commerce by: Deployment (Value)
        • 7.2.3.1. Cloud-Based (Private Cloud, Public Cloud)
        • 7.2.3.2. On-premises
      • 7.2.4. Global Big Data in E-Commerce by: Solution (Value)
        • 7.2.4.1. Customer Analytics
        • 7.2.4.2. Content Analytics
        • 7.2.4.3. Risk Management
        • 7.2.4.4. Fraud Detection
        • 7.2.4.5. Others
      • 7.2.5. Global Big Data in E-Commerce Region
        • 7.2.5.1. South America
          • 7.2.5.1.1. Brazil
          • 7.2.5.1.2. Argentina
          • 7.2.5.1.3. Rest of South America
        • 7.2.5.2. Asia Pacific
          • 7.2.5.2.1. China
          • 7.2.5.2.2. Japan
          • 7.2.5.2.3. India
          • 7.2.5.2.4. South Korea
          • 7.2.5.2.5. Taiwan
          • 7.2.5.2.6. Australia
          • 7.2.5.2.7. Rest of Asia-Pacific
        • 7.2.5.3. Europe
          • 7.2.5.3.1. Germany
          • 7.2.5.3.2. France
          • 7.2.5.3.3. Italy
          • 7.2.5.3.4. United Kingdom
          • 7.2.5.3.5. Netherlands
          • 7.2.5.3.6. Rest of Europe
        • 7.2.5.4. MEA
          • 7.2.5.4.1. Middle East
          • 7.2.5.4.2. Africa
        • 7.2.5.5. North America
          • 7.2.5.5.1. United States
          • 7.2.5.5.2. Canada
          • 7.2.5.5.3. Mexico
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Big Data in E-Commerce: by Application(USD Million)
  • Table 2. Big Data in E-Commerce Inventory , by Region USD Million (2015-2020)
  • Table 3. Big Data in E-Commerce Supply Chain , by Region USD Million (2015-2020)
  • Table 4. Big Data in E-Commerce Forecasting , by Region USD Million (2015-2020)
  • Table 5. Big Data in E-Commerce Pricing Strategies , by Region USD Million (2015-2020)
  • Table 6. Big Data in E-Commerce Sales , by Region USD Million (2015-2020)
  • Table 7. Big Data in E-Commerce Others , by Region USD Million (2015-2020)
  • Table 8. Big Data in E-Commerce: by Components(USD Million)
  • Table 9. Big Data in E-Commerce Hardware , by Region USD Million (2015-2020)
  • Table 10. Big Data in E-Commerce Software , by Region USD Million (2015-2020)
  • Table 11. Big Data in E-Commerce: by Deployment(USD Million)
  • Table 12. Big Data in E-Commerce Cloud-Based (Private Cloud, Public Cloud) , by Region USD Million (2015-2020)
  • Table 13. Big Data in E-Commerce On-premises , by Region USD Million (2015-2020)
  • Table 14. Big Data in E-Commerce: by Solution(USD Million)
  • Table 15. Big Data in E-Commerce Customer Analytics , by Region USD Million (2015-2020)
  • Table 16. Big Data in E-Commerce Content Analytics , by Region USD Million (2015-2020)
  • Table 17. Big Data in E-Commerce Risk Management , by Region USD Million (2015-2020)
  • Table 18. Big Data in E-Commerce Fraud Detection , by Region USD Million (2015-2020)
  • Table 19. Big Data in E-Commerce Others , by Region USD Million (2015-2020)
  • Table 20. South America Big Data in E-Commerce, by Country USD Million (2015-2020)
  • Table 21. South America Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 22. South America Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 23. South America Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 24. South America Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 25. Brazil Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 26. Brazil Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 27. Brazil Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 28. Brazil Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 29. Argentina Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 30. Argentina Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 31. Argentina Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 32. Argentina Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 33. Rest of South America Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 34. Rest of South America Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 35. Rest of South America Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 36. Rest of South America Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 37. Asia Pacific Big Data in E-Commerce, by Country USD Million (2015-2020)
  • Table 38. Asia Pacific Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 39. Asia Pacific Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 40. Asia Pacific Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 41. Asia Pacific Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 42. China Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 43. China Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 44. China Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 45. China Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 46. Japan Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 47. Japan Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 48. Japan Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 49. Japan Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 50. India Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 51. India Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 52. India Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 53. India Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 54. South Korea Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 55. South Korea Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 56. South Korea Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 57. South Korea Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 58. Taiwan Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 59. Taiwan Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 60. Taiwan Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 61. Taiwan Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 62. Australia Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 63. Australia Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 64. Australia Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 65. Australia Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 66. Rest of Asia-Pacific Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 67. Rest of Asia-Pacific Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 68. Rest of Asia-Pacific Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 69. Rest of Asia-Pacific Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 70. Europe Big Data in E-Commerce, by Country USD Million (2015-2020)
  • Table 71. Europe Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 72. Europe Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 73. Europe Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 74. Europe Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 75. Germany Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 76. Germany Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 77. Germany Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 78. Germany Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 79. France Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 80. France Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 81. France Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 82. France Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 83. Italy Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 84. Italy Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 85. Italy Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 86. Italy Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 87. United Kingdom Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 88. United Kingdom Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 89. United Kingdom Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 90. United Kingdom Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 91. Netherlands Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 92. Netherlands Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 93. Netherlands Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 94. Netherlands Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 95. Rest of Europe Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 96. Rest of Europe Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 97. Rest of Europe Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 98. Rest of Europe Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 99. MEA Big Data in E-Commerce, by Country USD Million (2015-2020)
  • Table 100. MEA Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 101. MEA Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 102. MEA Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 103. MEA Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 104. Middle East Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 105. Middle East Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 106. Middle East Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 107. Middle East Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 108. Africa Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 109. Africa Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 110. Africa Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 111. Africa Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 112. North America Big Data in E-Commerce, by Country USD Million (2015-2020)
  • Table 113. North America Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 114. North America Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 115. North America Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 116. North America Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 117. United States Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 118. United States Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 119. United States Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 120. United States Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 121. Canada Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 122. Canada Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 123. Canada Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 124. Canada Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 125. Mexico Big Data in E-Commerce, by Application USD Million (2015-2020)
  • Table 126. Mexico Big Data in E-Commerce, by Components USD Million (2015-2020)
  • Table 127. Mexico Big Data in E-Commerce, by Deployment USD Million (2015-2020)
  • Table 128. Mexico Big Data in E-Commerce, by Solution USD Million (2015-2020)
  • Table 129. Company Basic Information, Sales Area and Its Competitors
  • Table 130. Company Basic Information, Sales Area and Its Competitors
  • Table 131. Company Basic Information, Sales Area and Its Competitors
  • Table 132. Company Basic Information, Sales Area and Its Competitors
  • Table 133. Company Basic Information, Sales Area and Its Competitors
  • Table 134. Company Basic Information, Sales Area and Its Competitors
  • Table 135. Company Basic Information, Sales Area and Its Competitors
  • Table 136. Company Basic Information, Sales Area and Its Competitors
  • Table 137. Company Basic Information, Sales Area and Its Competitors
  • Table 138. Company Basic Information, Sales Area and Its Competitors
  • Table 139. Company Basic Information, Sales Area and Its Competitors
  • Table 140. Company Basic Information, Sales Area and Its Competitors
  • Table 141. Big Data in E-Commerce: by Application(USD Million)
  • Table 142. Big Data in E-Commerce Inventory , by Region USD Million (2021-2026)
  • Table 143. Big Data in E-Commerce Supply Chain , by Region USD Million (2021-2026)
  • Table 144. Big Data in E-Commerce Forecasting , by Region USD Million (2021-2026)
  • Table 145. Big Data in E-Commerce Pricing Strategies , by Region USD Million (2021-2026)
  • Table 146. Big Data in E-Commerce Sales , by Region USD Million (2021-2026)
  • Table 147. Big Data in E-Commerce Others , by Region USD Million (2021-2026)
  • Table 148. Big Data in E-Commerce: by Components(USD Million)
  • Table 149. Big Data in E-Commerce Hardware , by Region USD Million (2021-2026)
  • Table 150. Big Data in E-Commerce Software , by Region USD Million (2021-2026)
  • Table 151. Big Data in E-Commerce: by Deployment(USD Million)
  • Table 152. Big Data in E-Commerce Cloud-Based (Private Cloud, Public Cloud) , by Region USD Million (2021-2026)
  • Table 153. Big Data in E-Commerce On-premises , by Region USD Million (2021-2026)
  • Table 154. Big Data in E-Commerce: by Solution(USD Million)
  • Table 155. Big Data in E-Commerce Customer Analytics , by Region USD Million (2021-2026)
  • Table 156. Big Data in E-Commerce Content Analytics , by Region USD Million (2021-2026)
  • Table 157. Big Data in E-Commerce Risk Management , by Region USD Million (2021-2026)
  • Table 158. Big Data in E-Commerce Fraud Detection , by Region USD Million (2021-2026)
  • Table 159. Big Data in E-Commerce Others , by Region USD Million (2021-2026)
  • Table 160. South America Big Data in E-Commerce, by Country USD Million (2021-2026)
  • Table 161. South America Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 162. South America Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 163. South America Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 164. South America Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 165. Brazil Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 166. Brazil Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 167. Brazil Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 168. Brazil Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 169. Argentina Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 170. Argentina Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 171. Argentina Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 172. Argentina Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 173. Rest of South America Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 174. Rest of South America Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 175. Rest of South America Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 176. Rest of South America Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 177. Asia Pacific Big Data in E-Commerce, by Country USD Million (2021-2026)
  • Table 178. Asia Pacific Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 179. Asia Pacific Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 180. Asia Pacific Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 181. Asia Pacific Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 182. China Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 183. China Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 184. China Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 185. China Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 186. Japan Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 187. Japan Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 188. Japan Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 189. Japan Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 190. India Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 191. India Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 192. India Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 193. India Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 194. South Korea Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 195. South Korea Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 196. South Korea Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 197. South Korea Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 198. Taiwan Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 199. Taiwan Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 200. Taiwan Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 201. Taiwan Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 202. Australia Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 203. Australia Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 204. Australia Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 205. Australia Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 206. Rest of Asia-Pacific Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 207. Rest of Asia-Pacific Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 208. Rest of Asia-Pacific Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 209. Rest of Asia-Pacific Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 210. Europe Big Data in E-Commerce, by Country USD Million (2021-2026)
  • Table 211. Europe Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 212. Europe Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 213. Europe Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 214. Europe Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 215. Germany Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 216. Germany Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 217. Germany Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 218. Germany Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 219. France Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 220. France Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 221. France Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 222. France Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 223. Italy Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 224. Italy Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 225. Italy Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 226. Italy Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 227. United Kingdom Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 228. United Kingdom Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 229. United Kingdom Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 230. United Kingdom Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 231. Netherlands Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 232. Netherlands Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 233. Netherlands Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 234. Netherlands Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 235. Rest of Europe Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 236. Rest of Europe Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 237. Rest of Europe Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 238. Rest of Europe Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 239. MEA Big Data in E-Commerce, by Country USD Million (2021-2026)
  • Table 240. MEA Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 241. MEA Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 242. MEA Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 243. MEA Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 244. Middle East Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 245. Middle East Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 246. Middle East Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 247. Middle East Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 248. Africa Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 249. Africa Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 250. Africa Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 251. Africa Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 252. North America Big Data in E-Commerce, by Country USD Million (2021-2026)
  • Table 253. North America Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 254. North America Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 255. North America Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 256. North America Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 257. United States Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 258. United States Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 259. United States Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 260. United States Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 261. Canada Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 262. Canada Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 263. Canada Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 264. Canada Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 265. Mexico Big Data in E-Commerce, by Application USD Million (2021-2026)
  • Table 266. Mexico Big Data in E-Commerce, by Components USD Million (2021-2026)
  • Table 267. Mexico Big Data in E-Commerce, by Deployment USD Million (2021-2026)
  • Table 268. Mexico Big Data in E-Commerce, by Solution USD Million (2021-2026)
  • Table 269. Research Programs/Design for This Report
  • Table 270. Key Data Information from Secondary Sources
  • Table 271. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Big Data in E-Commerce: by Application USD Million (2015-2020)
  • Figure 5. Global Big Data in E-Commerce: by Components USD Million (2015-2020)
  • Figure 6. Global Big Data in E-Commerce: by Deployment USD Million (2015-2020)
  • Figure 7. Global Big Data in E-Commerce: by Solution USD Million (2015-2020)
  • Figure 8. South America Big Data in E-Commerce Share (%), by Country
  • Figure 9. Asia Pacific Big Data in E-Commerce Share (%), by Country
  • Figure 10. Europe Big Data in E-Commerce Share (%), by Country
  • Figure 11. MEA Big Data in E-Commerce Share (%), by Country
  • Figure 12. North America Big Data in E-Commerce Share (%), by Country
  • Figure 13. Global Big Data in E-Commerce share by Players 2020 (%)
  • Figure 14. Global Big Data in E-Commerce share by Players (Top 3) 2020(%)
  • Figure 15. Global Big Data in E-Commerce share by Players (Top 5) 2020(%)
  • Figure 16. BCG Matrix for key Companies
  • Figure 17. Amazon Web Services (United States) Revenue, Net Income and Gross profit
  • Figure 18. Amazon Web Services (United States) Revenue: by Geography 2020
  • Figure 19. Cloudera, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 20. Cloudera, Inc. (United States) Revenue: by Geography 2020
  • Figure 21. Hewlett Packard Enterprise Company (United States) Revenue, Net Income and Gross profit
  • Figure 22. Hewlett Packard Enterprise Company (United States) Revenue: by Geography 2020
  • Figure 23. Hitachi, Ltd. (Japan) Revenue, Net Income and Gross profit
  • Figure 24. Hitachi, Ltd. (Japan) Revenue: by Geography 2020
  • Figure 25. IBM (United States) Revenue, Net Income and Gross profit
  • Figure 26. IBM (United States) Revenue: by Geography 2020
  • Figure 27. Microsoft Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 28. Microsoft Corporation (United States) Revenue: by Geography 2020
  • Figure 29. Oracle Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 30. Oracle Corporation (United States) Revenue: by Geography 2020
  • Figure 31. Palantir Technologies (United States) Revenue, Net Income and Gross profit
  • Figure 32. Palantir Technologies (United States) Revenue: by Geography 2020
  • Figure 33. SAP SE (Germany) Revenue, Net Income and Gross profit
  • Figure 34. SAP SE (Germany) Revenue: by Geography 2020
  • Figure 35. Splunk Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 36. Splunk Inc. (United States) Revenue: by Geography 2020
  • Figure 37. SAS Institute (United States) Revenue, Net Income and Gross profit
  • Figure 38. SAS Institute (United States) Revenue: by Geography 2020
  • Figure 39. Teradata Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 40. Teradata Corporation (United States) Revenue: by Geography 2020
  • Figure 41. Global Big Data in E-Commerce: by Application USD Million (2021-2026)
  • Figure 42. Global Big Data in E-Commerce: by Components USD Million (2021-2026)
  • Figure 43. Global Big Data in E-Commerce: by Deployment USD Million (2021-2026)
  • Figure 44. Global Big Data in E-Commerce: by Solution USD Million (2021-2026)
  • Figure 45. South America Big Data in E-Commerce Share (%), by Country
  • Figure 46. Asia Pacific Big Data in E-Commerce Share (%), by Country
  • Figure 47. Europe Big Data in E-Commerce Share (%), by Country
  • Figure 48. MEA Big Data in E-Commerce Share (%), by Country
  • Figure 49. North America Big Data in E-Commerce Share (%), by Country
List of companies from research coverage that are profiled in the study
  • Amazon Web Services (United States)
  • Cloudera, Inc. (United States)
  • Hewlett Packard Enterprise Company (United States)
  • Hitachi, Ltd. (Japan)
  • IBM (United States)
  • Microsoft Corporation (United States)
  • Oracle Corporation (United States)
  • Palantir Technologies (United States)
  • SAP SE (Germany)
  • Splunk Inc. (United States)
  • SAS Institute (United States)
  • Teradata Corporation (United States)
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Key Highlights of Report


Mar 2022 233 Pages 86 Tables Base Year: 2021 Coverage: 15+ Companies; 18 Countries

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Global Big Data in E-Commerce Market Quantitative research analysis
Global Big Data in E-Commerce Market Qualitative Industry Analysis
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Frequently Asked Questions (FAQ):

The standard version of the report profiles players such as Amazon Web Services (United States), Cloudera, Inc. (United States), Hewlett Packard Enterprise Company (United States), Hitachi, Ltd. (Japan), IBM (United States), Microsoft Corporation (United States), Oracle Corporation (United States), Palantir Technologies (United States), SAP SE (Germany), Splunk Inc. (United States), SAS Institute (United States) and Teradata Corporation (United States) etc.
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Analysts at AMA estimates Big Data in E-Commerce Market to reach USD Million by 2026.

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