Big Data in E-commerce - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030

Publication ID:

PB511249108

Publication Date:

November 27, 2024

Pages:

108

Publisher:

MRRPB5

Countries:

Global [1]

USD 3,950.00

IT Services [2]

Computing & Electronics [3]

Description:

Software and services that analyze e-commerce through big data.
The global market for Big Data in E-commerce was estimated to be worth US$ million in 2023 and is forecast to a readjusted size of US$ million by 2030 with a CAGR of % during the forecast period 2024-2030.
According to International Telecommunication Union (ITU), the global Internet users (online population) were more than 5 billion. And the number of online shoppers was also increasing. In 2022, the global e-commerce market penetration rate increased to 19.7%, and the e-commerce market reached $5.5 trillion. At the same time, the Asian e-commerce market ranked at the top of the revenue ranking, which has reached $1.8 trillion. According to the National Bureau of Statistics, China was the largest online retail market in 2022, with online retail sales of 13.79 trillion yuan and a year-on-year increase of 4%. Among them, the online retail sales of physical goods were 11.96 trillion yuan, with a year-on-year increase of 6.2%, which accounted for 27.2% of the total retail sales of consumer goods.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Big Data in E-commerce, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Big Data in E-commerce by region & country, by Type, and by Application.
The Big Data in E-commerce market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Big Data in E-commerce.
Market Segmentation
By Company
Amazon Web Services, Inc.
Data Inc
Dell Inc.
Hewlett Packard Enterprise
Hitachi, Ltd.
IBM Corp.
Microsoft Corp.
Oracle Corp.
Palantir Technologies, Inc.
SAS Institute Inc.
Splunk Inc.
Teradata Corp.
Segment by Type:
Structured Big Data
Unstructured Big Data
Semi-structured Big Data
Segment by Application
Online Classifieds
Online Education
Online Financials
Online Retail
Online Travel and Leisure
By Region
North America
United States
Canada
Europe
Germany
France
U.K.
Italy
Russia
Asia-Pacific
China
Japan
South Korea
China Taiwan
Southeast Asia
India
Latin America
Mexico
Brazil
Argentina
Middle East & Africa
Turkey
Saudi Arabia
UAE
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Big Data in E-commerce manufacturers competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of Big Data in E-commerce in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Big Data in E-commerce in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Market Overview
1.1 Big Data in E-commerce Product Introduction
1.2 Global Big Data in E-commerce Market Size Forecast
1.3 Big Data in E-commerce Market Trends & Drivers
1.3.1 Big Data in E-commerce Industry Trends
1.3.2 Big Data in E-commerce Market Drivers & Opportunity
1.3.3 Big Data in E-commerce Market Challenges
1.3.4 Big Data in E-commerce Market Restraints
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Competitive Analysis by Company
2.1 Global Big Data in E-commerce Players Revenue Ranking (2023)
2.2 Global Big Data in E-commerce Revenue by Company (2019-2024)
2.3 Key Companies Big Data in E-commerce Manufacturing Base Distribution and Headquarters
2.4 Key Companies Big Data in E-commerce Product Offered
2.5 Key Companies Time to Begin Mass Production of Big Data in E-commerce
2.6 Big Data in E-commerce Market Competitive Analysis
2.6.1 Big Data in E-commerce Market Concentration Rate (2019-2024)
2.6.2 Global 5 and 10 Largest Companies by Big Data in E-commerce Revenue in 2023
2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Big Data in E-commerce as of 2023)
2.7 Mergers & Acquisitions, Expansion
3 Segmentation by Type
3.1 Introduction by Type
3.1.1 Structured Big Data
3.1.2 Unstructured Big Data
3.1.3 Semi-structured Big Data
3.2 Global Big Data in E-commerce Sales Value by Type
3.2.1 Global Big Data in E-commerce Sales Value by Type (2019 VS 2023 VS 2030)
3.2.2 Global Big Data in E-commerce Sales Value, by Type (2019-2030)
3.2.3 Global Big Data in E-commerce Sales Value, by Type (%) (2019-2030)
4 Segmentation by Application
4.1 Introduction by Application
4.1.1 Online Classifieds
4.1.2 Online Education
4.1.3 Online Financials
4.1.4 Online Retail
4.1.5 Online Travel and Leisure
4.2 Global Big Data in E-commerce Sales Value by Application
4.2.1 Global Big Data in E-commerce Sales Value by Application (2019 VS 2023 VS 2030)
4.2.2 Global Big Data in E-commerce Sales Value, by Application (2019-2030)
4.2.3 Global Big Data in E-commerce Sales Value, by Application (%) (2019-2030)
5 Segmentation by Region
5.1 Global Big Data in E-commerce Sales Value by Region
5.1.1 Global Big Data in E-commerce Sales Value by Region: 2019 VS 2023 VS 2030
5.1.2 Global Big Data in E-commerce Sales Value by Region (2019-2024)
5.1.3 Global Big Data in E-commerce Sales Value by Region (2025-2030)
5.1.4 Global Big Data in E-commerce Sales Value by Region (%), (2019-2030)
5.2 North America
5.2.1 North America Big Data in E-commerce Sales Value, 2019-2030
5.2.2 North America Big Data in E-commerce Sales Value by Country (%), 2023 VS 2030
5.3 Europe
5.3.1 Europe Big Data in E-commerce Sales Value, 2019-2030
5.3.2 Europe Big Data in E-commerce Sales Value by Country (%), 2023 VS 2030
5.4 Asia Pacific
5.4.1 Asia Pacific Big Data in E-commerce Sales Value, 2019-2030
5.4.2 Asia Pacific Big Data in E-commerce Sales Value by Country (%), 2023 VS 2030
5.5 South America
5.5.1 South America Big Data in E-commerce Sales Value, 2019-2030
5.5.2 South America Big Data in E-commerce Sales Value by Country (%), 2023 VS 2030
5.6 Middle East & Africa
5.6.1 Middle East & Africa Big Data in E-commerce Sales Value, 2019-2030
5.6.2 Middle East & Africa Big Data in E-commerce Sales Value by Country (%), 2023 VS 2030
6 Segmentation by Key Countries/Regions
6.1 Key Countries/Regions Big Data in E-commerce Sales Value Growth Trends, 2019 VS 2023 VS 2030
6.2 Key Countries/Regions Big Data in E-commerce Sales Value
6.3 United States
6.3.1 United States Big Data in E-commerce Sales Value, 2019-2030
6.3.2 United States Big Data in E-commerce Sales Value by Type (%), 2023 VS 2030
6.3.3 United States Big Data in E-commerce Sales Value by Application, 2023 VS 2030
6.4 Europe
6.4.1 Europe Big Data in E-commerce Sales Value, 2019-2030
6.4.2 Europe Big Data in E-commerce Sales Value by Type (%), 2023 VS 2030
6.4.3 Europe Big Data in E-commerce Sales Value by Application, 2023 VS 2030
6.5 China
6.5.1 China Big Data in E-commerce Sales Value, 2019-2030
6.5.2 China Big Data in E-commerce Sales Value by Type (%), 2023 VS 2030
6.5.3 China Big Data in E-commerce Sales Value by Application, 2023 VS 2030
6.6 Japan
6.6.1 Japan Big Data in E-commerce Sales Value, 2019-2030
6.6.2 Japan Big Data in E-commerce Sales Value by Type (%), 2023 VS 2030
6.6.3 Japan Big Data in E-commerce Sales Value by Application, 2023 VS 2030
6.7 South Korea
6.7.1 South Korea Big Data in E-commerce Sales Value, 2019-2030
6.7.2 South Korea Big Data in E-commerce Sales Value by Type (%), 2023 VS 2030
6.7.3 South Korea Big Data in E-commerce Sales Value by Application, 2023 VS 2030
6.8 Southeast Asia
6.8.1 Southeast Asia Big Data in E-commerce Sales Value, 2019-2030
6.8.2 Southeast Asia Big Data in E-commerce Sales Value by Type (%), 2023 VS 2030
6.8.3 Southeast Asia Big Data in E-commerce Sales Value by Application, 2023 VS 2030
6.9 India
6.9.1 India Big Data in E-commerce Sales Value, 2019-2030
6.9.2 India Big Data in E-commerce Sales Value by Type (%), 2023 VS 2030
6.9.3 India Big Data in E-commerce Sales Value by Application, 2023 VS 2030
7 Company Profiles
7.1 Amazon Web Services, Inc.
7.1.1 Amazon Web Services, Inc. Profile
7.1.2 Amazon Web Services, Inc. Main Business
7.1.3 Amazon Web Services, Inc. Big Data in E-commerce Products, Services and Solutions
7.1.4 Amazon Web Services, Inc. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.1.5 Amazon Web Services, Inc. Recent Developments
7.2 Data Inc
7.2.1 Data Inc Profile
7.2.2 Data Inc Main Business
7.2.3 Data Inc Big Data in E-commerce Products, Services and Solutions
7.2.4 Data Inc Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.2.5 Data Inc Recent Developments
7.3 Dell Inc.
7.3.1 Dell Inc. Profile
7.3.2 Dell Inc. Main Business
7.3.3 Dell Inc. Big Data in E-commerce Products, Services and Solutions
7.3.4 Dell Inc. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.3.5 Hewlett Packard Enterprise Recent Developments
7.4 Hewlett Packard Enterprise
7.4.1 Hewlett Packard Enterprise Profile
7.4.2 Hewlett Packard Enterprise Main Business
7.4.3 Hewlett Packard Enterprise Big Data in E-commerce Products, Services and Solutions
7.4.4 Hewlett Packard Enterprise Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.4.5 Hewlett Packard Enterprise Recent Developments
7.5 Hitachi, Ltd.
7.5.1 Hitachi, Ltd. Profile
7.5.2 Hitachi, Ltd. Main Business
7.5.3 Hitachi, Ltd. Big Data in E-commerce Products, Services and Solutions
7.5.4 Hitachi, Ltd. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.5.5 Hitachi, Ltd. Recent Developments
7.6 IBM Corp.
7.6.1 IBM Corp. Profile
7.6.2 IBM Corp. Main Business
7.6.3 IBM Corp. Big Data in E-commerce Products, Services and Solutions
7.6.4 IBM Corp. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.6.5 IBM Corp. Recent Developments
7.7 Microsoft Corp.
7.7.1 Microsoft Corp. Profile
7.7.2 Microsoft Corp. Main Business
7.7.3 Microsoft Corp. Big Data in E-commerce Products, Services and Solutions
7.7.4 Microsoft Corp. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.7.5 Microsoft Corp. Recent Developments
7.8 Oracle Corp.
7.8.1 Oracle Corp. Profile
7.8.2 Oracle Corp. Main Business
7.8.3 Oracle Corp. Big Data in E-commerce Products, Services and Solutions
7.8.4 Oracle Corp. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.8.5 Oracle Corp. Recent Developments
7.9 Palantir Technologies, Inc.
7.9.1 Palantir Technologies, Inc. Profile
7.9.2 Palantir Technologies, Inc. Main Business
7.9.3 Palantir Technologies, Inc. Big Data in E-commerce Products, Services and Solutions
7.9.4 Palantir Technologies, Inc. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.9.5 Palantir Technologies, Inc. Recent Developments
7.10 SAS Institute Inc.
7.10.1 SAS Institute Inc. Profile
7.10.2 SAS Institute Inc. Main Business
7.10.3 SAS Institute Inc. Big Data in E-commerce Products, Services and Solutions
7.10.4 SAS Institute Inc. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.10.5 SAS Institute Inc. Recent Developments
7.11 Splunk Inc.
7.11.1 Splunk Inc. Profile
7.11.2 Splunk Inc. Main Business
7.11.3 Splunk Inc. Big Data in E-commerce Products, Services and Solutions
7.11.4 Splunk Inc. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.11.5 Splunk Inc. Recent Developments
7.12 Teradata Corp.
7.12.1 Teradata Corp. Profile
7.12.2 Teradata Corp. Main Business
7.12.3 Teradata Corp. Big Data in E-commerce Products, Services and Solutions
7.12.4 Teradata Corp. Big Data in E-commerce Revenue (US$ Million) & (2019-2024)
7.12.5 Teradata Corp. Recent Developments
8 Industry Chain Analysis
8.1 Big Data in E-commerce Industrial Chain
8.2 Big Data in E-commerce Upstream Analysis
8.2.1 Key Raw Materials
8.2.2 Raw Materials Key Suppliers
8.2.3 Manufacturing Cost Structure
8.3 Midstream Analysis
8.4 Downstream Analysis (Customers Analysis)
8.5 Sales Model and Sales Channels
8.5.1 Big Data in E-commerce Sales Model
8.5.2 Sales Channel
8.5.3 Big Data in E-commerce Distributors
9 Research Findings and Conclusion
10 Appendix
10.1 Research Methodology
10.1.1 Methodology/Research Approach
10.1.2 Data Source
10.2 Author Details
10.3 Disclaimer

Companies Mentioned:

Amazon Web Services, Inc.
Data Inc
Dell Inc.
Hewlett Packard Enterprise
Hitachi, Ltd.
IBM Corp.
Microsoft Corp.
Oracle Corp.
Palantir Technologies, Inc.
SAS Institute Inc.
Splunk Inc.
Teradata Corp.

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