Global Big Data for Automotive Market Research Report 2024

Publication ID:

PB508245287

Publication Date:

August 12, 2024

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

Big data analytics allows the automobile manufacturing industry to collect data from ERP systems to combine information from multiple functional units of the business and the supply chain members.
The global Big Data for Automotive market was valued at US$ million in 2023 and is anticipated to reach US$ million by 2030, witnessing a CAGR of % during the forecast period 2024-2030.
Automotive is a key driver of this industry. According to data from the World Automobile Organization (OICA), global automobile production and sales in 2017 reached their peak in the past 10 years, at 97.3 million and 95.89 million respectively. In 2018, the global economic expansion ended, and the global auto market declined as a whole. In 2022, there will wear units 81.6 million vehicles in the world. At present, more than 90% of the world's automobiles are concentrated in the three continents of Asia, Europe and North America, of which Asia automobile production accounts for 56% of the world, Europe accounts for 20%, and North America accounts for 16%. The world major automobile producing countries include China, the United States, Japan, South Korea, Germany, India, Mexico, and other countries; among them, China is the largest automobile producing country in the world, accounting for about 32%. Japan is the world's largest car exporter, exporting more than 3.5 million vehicles in 2022.
This report aims to provide a comprehensive presentation of the global market for Big Data for Automotive, 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 for Automotive.
Report Scope
The Big Data for Automotive market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Big Data for Automotive market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Big Data for Automotive companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
IBM
SAP SE
Microsoft
National Instruments
N-iX LTD
Future Processing
Reply SpA
Phocas
Positive Thinking Company
Qburst Technologies
Monixo
Allerin Tech
Driver Design Studio
Sight Machine
SAS Institute
Segment by Type
For Product Development
For Supply Chain
For Manufacturing
Segment by Application
OEM
Aftermarket
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Big Data for Automotive companies鈥� competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: 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 5: 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 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.

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

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Big Data for Automotive Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 For Product Development
1.2.3 For Supply Chain
1.2.4 For Manufacturing
1.3 Market by Application
1.3.1 Global Big Data for Automotive Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 OEM
1.3.3 Aftermarket
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Big Data for Automotive Market Perspective (2019-2030)
2.2 Big Data for Automotive Growth Trends by Region
2.2.1 Global Big Data for Automotive Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Big Data for Automotive Historic Market Size by Region (2019-2024)
2.2.3 Big Data for Automotive Forecasted Market Size by Region (2025-2030)
2.3 Big Data for Automotive Market Dynamics
2.3.1 Big Data for Automotive Industry Trends
2.3.2 Big Data for Automotive Market Drivers
2.3.3 Big Data for Automotive Market Challenges
2.3.4 Big Data for Automotive Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Big Data for Automotive Players by Revenue
3.1.1 Global Top Big Data for Automotive Players by Revenue (2019-2024)
3.1.2 Global Big Data for Automotive Revenue Market Share by Players (2019-2024)
3.2 Global Big Data for Automotive Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Big Data for Automotive Revenue
3.4 Global Big Data for Automotive Market Concentration Ratio
3.4.1 Global Big Data for Automotive Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Big Data for Automotive Revenue in 2023
3.5 Big Data for Automotive Key Players Head office and Area Served
3.6 Key Players Big Data for Automotive Product Solution and Service
3.7 Date of Enter into Big Data for Automotive Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Big Data for Automotive Breakdown Data by Type
4.1 Global Big Data for Automotive Historic Market Size by Type (2019-2024)
4.2 Global Big Data for Automotive Forecasted Market Size by Type (2025-2030)
5 Big Data for Automotive Breakdown Data by Application
5.1 Global Big Data for Automotive Historic Market Size by Application (2019-2024)
5.2 Global Big Data for Automotive Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Big Data for Automotive Market Size (2019-2030)
6.2 North America Big Data for Automotive Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Big Data for Automotive Market Size by Country (2019-2024)
6.4 North America Big Data for Automotive Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Big Data for Automotive Market Size (2019-2030)
7.2 Europe Big Data for Automotive Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Big Data for Automotive Market Size by Country (2019-2024)
7.4 Europe Big Data for Automotive Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Big Data for Automotive Market Size (2019-2030)
8.2 Asia-Pacific Big Data for Automotive Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Big Data for Automotive Market Size by Region (2019-2024)
8.4 Asia-Pacific Big Data for Automotive Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Big Data for Automotive Market Size (2019-2030)
9.2 Latin America Big Data for Automotive Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Big Data for Automotive Market Size by Country (2019-2024)
9.4 Latin America Big Data for Automotive Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Big Data for Automotive Market Size (2019-2030)
10.2 Middle East & Africa Big Data for Automotive Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Big Data for Automotive Market Size by Country (2019-2024)
10.4 Middle East & Africa Big Data for Automotive Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 IBM
11.1.1 IBM Company Detail
11.1.2 IBM Business Overview
11.1.3 IBM Big Data for Automotive Introduction
11.1.4 IBM Revenue in Big Data for Automotive Business (2019-2024)
11.1.5 IBM Recent Development
11.2 SAP SE
11.2.1 SAP SE Company Detail
11.2.2 SAP SE Business Overview
11.2.3 SAP SE Big Data for Automotive Introduction
11.2.4 SAP SE Revenue in Big Data for Automotive Business (2019-2024)
11.2.5 SAP SE Recent Development
11.3 Microsoft
11.3.1 Microsoft Company Detail
11.3.2 Microsoft Business Overview
11.3.3 Microsoft Big Data for Automotive Introduction
11.3.4 Microsoft Revenue in Big Data for Automotive Business (2019-2024)
11.3.5 Microsoft Recent Development
11.4 National Instruments
11.4.1 National Instruments Company Detail
11.4.2 National Instruments Business Overview
11.4.3 National Instruments Big Data for Automotive Introduction
11.4.4 National Instruments Revenue in Big Data for Automotive Business (2019-2024)
11.4.5 National Instruments Recent Development
11.5 N-iX LTD
11.5.1 N-iX LTD Company Detail
11.5.2 N-iX LTD Business Overview
11.5.3 N-iX LTD Big Data for Automotive Introduction
11.5.4 N-iX LTD Revenue in Big Data for Automotive Business (2019-2024)
11.5.5 N-iX LTD Recent Development
11.6 Future Processing
11.6.1 Future Processing Company Detail
11.6.2 Future Processing Business Overview
11.6.3 Future Processing Big Data for Automotive Introduction
11.6.4 Future Processing Revenue in Big Data for Automotive Business (2019-2024)
11.6.5 Future Processing Recent Development
11.7 Reply SpA
11.7.1 Reply SpA Company Detail
11.7.2 Reply SpA Business Overview
11.7.3 Reply SpA Big Data for Automotive Introduction
11.7.4 Reply SpA Revenue in Big Data for Automotive Business (2019-2024)
11.7.5 Reply SpA Recent Development
11.8 Phocas
11.8.1 Phocas Company Detail
11.8.2 Phocas Business Overview
11.8.3 Phocas Big Data for Automotive Introduction
11.8.4 Phocas Revenue in Big Data for Automotive Business (2019-2024)
11.8.5 Phocas Recent Development
11.9 Positive Thinking Company
11.9.1 Positive Thinking Company Company Detail
11.9.2 Positive Thinking Company Business Overview
11.9.3 Positive Thinking Company Big Data for Automotive Introduction
11.9.4 Positive Thinking Company Revenue in Big Data for Automotive Business (2019-2024)
11.9.5 Positive Thinking Company Recent Development
11.10 Qburst Technologies
11.10.1 Qburst Technologies Company Detail
11.10.2 Qburst Technologies Business Overview
11.10.3 Qburst Technologies Big Data for Automotive Introduction
11.10.4 Qburst Technologies Revenue in Big Data for Automotive Business (2019-2024)
11.10.5 Qburst Technologies Recent Development
11.11 Monixo
11.11.1 Monixo Company Detail
11.11.2 Monixo Business Overview
11.11.3 Monixo Big Data for Automotive Introduction
11.11.4 Monixo Revenue in Big Data for Automotive Business (2019-2024)
11.11.5 Monixo Recent Development
11.12 Allerin Tech
11.12.1 Allerin Tech Company Detail
11.12.2 Allerin Tech Business Overview
11.12.3 Allerin Tech Big Data for Automotive Introduction
11.12.4 Allerin Tech Revenue in Big Data for Automotive Business (2019-2024)
11.12.5 Allerin Tech Recent Development
11.13 Driver Design Studio
11.13.1 Driver Design Studio Company Detail
11.13.2 Driver Design Studio Business Overview
11.13.3 Driver Design Studio Big Data for Automotive Introduction
11.13.4 Driver Design Studio Revenue in Big Data for Automotive Business (2019-2024)
11.13.5 Driver Design Studio Recent Development
11.14 Sight Machine
11.14.1 Sight Machine Company Detail
11.14.2 Sight Machine Business Overview
11.14.3 Sight Machine Big Data for Automotive Introduction
11.14.4 Sight Machine Revenue in Big Data for Automotive Business (2019-2024)
11.14.5 Sight Machine Recent Development
11.15 SAS Institute
11.15.1 SAS Institute Company Detail
11.15.2 SAS Institute Business Overview
11.15.3 SAS Institute Big Data for Automotive Introduction
11.15.4 SAS Institute Revenue in Big Data for Automotive Business (2019-2024)
11.15.5 SAS Institute Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details

Companies Mentioned:

IBM
SAP SE
Microsoft
National Instruments
N-iX LTD
Future Processing
Reply SpA
Phocas
Positive Thinking Company
Qburst Technologies
Monixo
Allerin Tech
Driver Design Studio
Sight Machine
SAS Institute

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