세계의 자동차용 데이터 관리 시장 규모 조사 및 예측 : 데이터 유형별, 소프트웨어 유형별, 지역별 분석(2023-2030년)

Global Automotive Data Management Market is valued approximately at USD 1.08 billion in 2022 and is anticipated to grow with a compounded annual growth rate of more than 20% over the forecast period 2023-2030. An Automotive Data Management System refers to the comprehensive software or hardware solution designed to collect, store process and analyze various types of data generated within automotive industry. It is a sophisticated system that helps to manage and organize large volume of data related to vehicles, costumers, operations and other aspects of automotive ecosystem. The primary purpose of an automated data management system is to enable efficient and effective data handling, ensuring that information is readily available for analysis, decision, making and operational purposes. It facilitates the integration of data from multiple sources such as vehicle sensors, manufacturing processes, supply chain system, customer interactions and more. Moreover, growing automotive industry and increasing use of IoT in automotive data management expected to be the growth factors of the Global Automotive Data Management market.

According to the India Brand Equity Foundation (IBEF) in 2021, the Indian passenger car market was valued at USD 32.70 billion and is expected to grow USD 54.84 billion by 2027. According to Statista in 2021, it was found that the number of connected automobiles in operation were 237 million and is anticipated to surpass 400 million by 2025. With the increasing integration of electronics in vehicles, over the past few decades, automotive industry possesses advanced capabilities to internally and externally monitor and record data. However, limited connectivity and regulatory and legal compliance may hamper the growth of global automotive, data management market. Moreover, increasing standard of living and increasing disposable income emerge as to be the growth opportunities for the market.

The key regions considered for the Global Automotive Data Management Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. Europe region dominated the market in 2022 owing to the factors such as early adaptation of advanced technology

and advancement in automotive industry. Europe is the home for many multinational automotive industries such as Volkswagen group AG, Stellantis NV, Mercedes-Benz group AG, Bayerische Motoren Werke AG (BMW) and so on. Asia-Pacific is expected to be the fastest growing region, owing to the factors such as low labor cost and large customer base. According to Press Information Bureau of India (PIB), contribution of automotive industry in GDP has been rose to 7.1% and India aims to double its automotive industry to USD 182.7 billion by 2024.

Major market players included in this report are:

• Acerta Analytics Solutions Inc.
• Amazon Web Services Inc.
• Amodo
• Caruso Gmbh
• ETL Solutions Ltd.
• HEAVY.AI
• International Business Machines Corporation.
• National Instruments Corporation
• SAP SE
• Teradata Corporation

Recent Developments in the Market:

• In January 2023, the establishment of Cofinity-X marks the next phase of progress in Europe for the advancement of the Catena-X initiative, led by major shareholders including BASF, BMW Group, Henkel, Mercedes-Benz, SAP , Schaeffler, Siemens, T-Systems, Volkswagen and ZF.
• In October 2022, Salesforce industries added Automotive Cloud CRM which provide a customer sales , service, marketing and commerce platform for cars and truck dealers manufacturers and financiers.

Global Automotive Data Management Market Report Scope:

• Historical Data: 2020 - 2021
• Base Year for Estimation: 2022
• Forecast period: 2023-2030
• Report Coverage: Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
• Segments Covered:Data Type, Software Type, Region
• Regional Scope: North America; Europe; Asia Pacific; Latin America; Middle East & Africa
• Customization Scope: Free report customization (equivalent up to 8 analyst's working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Data Type:

• Unstructured
• Semi-Structured & Structured

By Software Type:

• Data Security
• Data Integration
• Data Migration
• Data Quality

By Region:

• North America
• U.S.
• Canada
• Europe
• UK
• Germany
• France
• Spain
• Italy
• ROE
• Asia Pacific
• China
• India
• Japan
• Australia
• South Korea
• RoAPAC
• Latin America
• Brazil
• Mexico
• Middle East & Africa
• Saudi Arabia
• South Africa
• Rest of Middle East & Africa

Table of Contents

Chapter 1. Executive Summary

• 1.1. Market Snapshot
• 1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
  • 1.2.1. Automotive Data Management Market, by region, 2020-2030 (USD Billion)
  • 1.2.2. Automotive Data Management Market, by Data Type, 2020-2030 (USD Billion)
  • 1.2.3. Automotive Data Management Market, by Software Type, 2020-2030 (USD Billion)
• 1.3. Key Trends
• 1.4. Estimation Methodology
• 1.5. Research Assumption

Chapter 2. Global Automotive Data Management Market Definition and Scope

• 2.1. Objective of the Study
• 2.2. Market Definition & Scope
  • 2.2.1. Industry Evolution
  • 2.2.2. Scope of the Study
• 2.3. Years Considered for the Study
• 2.4. Currency Conversion Rates

Chapter 3. Global Automotive Data Management Market Dynamics

• 3.1. Automotive Data Management Market Impact Analysis (2020-2030)
  • 3.1.1. Market Drivers
    • 3.1.1.1. Growing Automotive Industry
    • 3.1.1.2. Increasing use of IoT Automotive Data Management
  • 3.1.2. Market Challenges
    • 3.1.2.1. Limited Connectivity
    • 3.1.2.2. Regulatory and Legal Compliance
  • 3.1.3. Market Opportunities
    • 3.1.3.1. Increasing Standard of Living
    • 3.1.3.2. Increasing Disposable Income

Chapter 4. Global Automotive Data Management Market: Industry Analysis

• 4.1. Porter's 5 Force Model
  • 4.1.1. Bargaining Power of Suppliers
  • 4.1.2. Bargaining Power of Buyers
  • 4.1.3. Threat of New Entrants
  • 4.1.4. Threat of Substitutes
  • 4.1.5. Competitive Rivalry
• 4.2. Porter's 5 Force Impact Analysis
• 4.3. PEST Analysis
  • 4.3.1. Political
  • 4.3.2. Economic
  • 4.3.3. Social
  • 4.3.4. Technological
  • 4.3.5. Environmental
  • 4.3.6. Legal
• 4.4. Top investment opportunity
• 4.5. Top winning strategies
• 4.6. COVID-19 Impact Analysis
• 4.7. Disruptive Trends
• 4.8. Industry Expert Perspective
• 4.9. Analyst Recommendation & Conclusion

Chapter 5. Global Automotive Data Management Market, by Data Type

• 5.1. Market Snapshot
• 5.2. Global Automotive Data Management Market by Data Type, Performance - Potential Analysis
• 5.3. Global Automotive Data Management Market Estimates & Forecasts by Data Type 2020-2030 (USD Billion)
• 5.4. Automotive Data Management Market, Sub Segment Analysis
  • 5.4.1. Unstructured
  • 5.4.2. Semi-Structured & Structured

Chapter 6. Global Automotive Data Management Market, by Software Type

• 6.1. Market Snapshot
• 6.2. Global Automotive Data Management Market by Software Type, Performance - Potential Analysis
• 6.3. Global Automotive Data Management Market Estimates & Forecasts by Software Type 2020-2030 (USD Billion)
• 6.4. Automotive Data Management Market, Sub Segment Analysis
  • 6.4.1. Data Security
  • 6.4.2. Data Integration
  • 6.4.3. Data Migration
  • 6.4.4. Data Quality

Chapter 7. Global Automotive Data Management Market, Regional Analysis

• 7.1. Top Leading Countries
• 7.2. Top Emerging Countries
• 7.3. Automotive Data Management Market, Regional Market Snapshot
• 7.4. North America Automotive Data Management Market
  • 7.4.1. U.S. Automotive Data Management Market
    • 7.4.1.1. Data Type breakdown estimates & forecasts, 2020-2030
    • 7.4.1.2. Software Type breakdown estimates & forecasts, 2020-2030
  • 7.4.2. Canada Automotive Data Management Market
• 7.5. Europe Automotive Data Management Market Snapshot
  • 7.5.1. U.K. Automotive Data Management Market
  • 7.5.2. Germany Automotive Data Management Market
  • 7.5.3. France Automotive Data Management Market
  • 7.5.4. Spain Automotive Data Management Market
  • 7.5.5. Italy Automotive Data Management Market
  • 7.5.6. Rest of Europe Automotive Data Management Market
• 7.6. Asia-Pacific Automotive Data Management Market Snapshot
  • 7.6.1. China Automotive Data Management Market
  • 7.6.2. India Automotive Data Management Market
  • 7.6.3. Japan Automotive Data Management Market
  • 7.6.4. Australia Automotive Data Management Market
  • 7.6.5. South Korea Automotive Data Management Market
  • 7.6.6. Rest of Asia Pacific Automotive Data Management Market
• 7.7. Latin America Automotive Data Management Market Snapshot
  • 7.7.1. Brazil Automotive Data Management Market
  • 7.7.2. Mexico Automotive Data Management Market
• 7.8. Middle East & Africa Automotive Data Management Market
  • 7.8.1. Saudi Arabia Automotive Data Management Market
  • 7.8.2. South Africa Automotive Data Management Market
  • 7.8.3. Rest of Middle East & Africa Automotive Data Management Market

Chapter 8. Competitive Intelligence

• 8.1. Key Company SWOT Analysis
  • 8.1.1. Company 1
  • 8.1.2. Company 2
  • 8.1.3. Company 3
• 8.2. Top Market Strategies
• 8.3. Company Profiles
  • 8.3.1. Acreta Analytics Solutions Inc.
    • 8.3.1.1. Key Information
    • 8.3.1.2. Overview
    • 8.3.1.3. Financial (Subject to Data Availability)
    • 8.3.1.4. Product Summary
    • 8.3.1.5. Recent Developments
  • 8.3.2. Amazon Web Services Inc.
  • 8.3.3. Amodo
  • 8.3.4. Caruso gmbh
  • 8.3.5. ETL Solutions Ltd.
  • 8.3.6. HEAVY.AI
  • 8.3.7. International Business Machines Corporation
  • 8.3.8. National Instruments Corporation
  • 8.3.9. SAP SE
  • 8.3.10. Teradata Corporation

Chapter 9. Research Process

• 9.1. Research Process
  • 9.1.1. Data Mining
  • 9.1.2. Analysis
  • 9.1.3. Market Estimation
  • 9.1.4. Validation
  • 9.1.5. Publishing
• 9.2. Research Attributes
• 9.3. Research Assumption