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Automotive Data Management Market Size, Share & Industry Trends Analysis Report By Component (Software and Services), By Data Type, By Application, By Deployment Type (Cloud and On-premise), By Vehicle Type, By Regional Outlook and Forecast, 2022 - 2028

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    Report

  • 313 Pages
  • November 2022
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5709619
The Global Automotive Data Management Market size is expected to reach $3.7 billion by 2028, rising at a market growth of 17.8% CAGR during the forecast period.

Data management is the process of gathering, storing, and utilizing information in a safe, efficient, and cost-effective manner. The purpose of data management is to assist individuals, organizations, and linked objects in optimizing the use of data within the constraints of policy and law so that they may maximize the organization's profit from choices and actions. As businesses increasingly rely on intangible assets to generate value, a solid data management strategy is becoming more crucial than ever.



Today's businesses require a data management system that effectively manages data across a heterogeneous yet unified data layer. Data management platforms serve as the foundation for data management systems, including databases, data lakes and warehouses, big data management systems, and data analytics, among others.

All of these components function as a "data utility"to provide the data management capabilities a company need for its applications, as well as the analytics and algorithms that utilize the data generated by those applications. Even though modern technologies assist database administrators (DBAs) in automating several conventional administration chores, manual intervention is frequently necessary due to the scale and complexity of most database deployments. When physical intervention is necessary, the possibility of mistakes increases. Reducing the need for human data administration is a fundamental purpose of the autonomous database, a novel data management system.

COVID-19 Impact Analysis

The COVID-19 pandemic had a huge influence on the market's expansion. The supply chain disruption hurt sales, delivery schedules, and manufacturing, resulting in a significant decline in automobile sales in 2020, and consequently a decline in the demand for automotive data management, which is dependent on the demand and sales of the automotive industry. Since 2021, however, the need for automotive data management has increased due to the growth of connected automobiles.

Market Growth Factors

Technological developments in the vehicle industry

The rising need for built-in informatics and telematics in the automobile industry has led to technological improvements targeted at enhancing the in-vehicle experience for both drivers and passengers. With the advent of the connected car, ubiquitous in-vehicle cellular connections offer new options for educating and engaging drivers, as well as servicing the vehicles throughout their lifetime. As software defines an increasing number of vehicle functions, the ability to upgrade software OTA (over the air) makes integrated cellular connectivity a critical means of maintaining vehicle security and relevance over the vehicle's lifespan.

Insurers are increasingly interested in usage-based insurance (UBI)

Usage-based insurance (UBI) is a form of insurance in which the premium is directly proportional to the amount of vehicle use. Insurers utilize analytics solutions to gain access to real-time car usage data to calculate premiums. Usage-Based Insurance (UBI) is a form of automobile insurance that monitors mileage and driving patterns. UBI is frequently powered by in-vehicle telecommunication devices (telematics) - technology that is accessible in a vehicle that is self-installed via a plug-in device or already incorporated as original equipment by car manufacturers.

Market Restraining Factors

Growing cases of the cyber breaches

As digital transformation has progressed, new cybersecurity risks have unavoidably emerged. Cybercriminals capitalize on the Covid-19 outbreak by targeting distant organizations and enterprises. Increasingly complex ransomware strategies are being adopted by threat actors to harm industrial processes in general, and the automobile industry in particular. Notably, specialists are observing an increase in the prevalence of incorporation systems (ICSes), which can migrate from IT networks to OT networks. Connected vehicles are one of the major contributors to these dangers

Component Outlook

Based on the Component, the Automotive Data Management Market is segmented into Software and Services. The software segment acquired the highest revenue share in the automotive data management market in 2021. This is due to the growing demand and use of automotive software among end-users such as fleet owners, transportation and logistics firms, and car manufacturers to track the vehicle.



Data Type Outlook

On the basis of Data Type, the Automotive Data Management Market is divided into Structured and Unstructured. The unstructured segment recorded a substantial revenue share in the automotive data management market in 2021. It is because Using LiDAR and other sensors, autonomous, connected, and non-autonomous cars collect a tremendous quantity of unstructured data. Market participants in the automotive industry are using cloud technologies to store unstructured vehicle data on the cloud. Unstructured data aids in the development of driverless vehicles.

Application Outlook

On the basis of Application, the Automotive Data Management Market is categorized into Predictive Maintenance, Warranty Analytics, Safety & Security Management, Driver & User Behavior Analysis, and Dealer Performance Analysis. The driver & user behavior analysis segment procured the highest revenue share in the automotive data management market in 2021. This segment's rise can be attributable to the many strategies deployed, such as monitoring the driver's physical condition with face recognition and monitoring of physical features, gathering navigation data using onboard telematics, and assessing driving patterns.

Deployment Type Outlook

Based on the Deployment Type, the Automotive Data Management Market is bifurcated into On-premise and Cloud. The on-premise segment witnessed a substantial revenue share in the automotive data management market in 2021. On-premise software is deployed on physical hardware that is owned by an organization, placed on the company's physical grounds, and typically in its own data center. Because the IT team can physically access the data, it has greater control over the server hardware and data setup, security, and administration.

Vehicle Type Outlook

By Vehicle Type, the Automotive Data Management Market is classified into Autonomous and Non-autonomous. The non-autonomous segment garnered the highest revenue share in the automotive data management market in 2021. It is because non-autonomous cars cannot operate without human assistance. Automotive data management has found application in linked non-autonomous vehicles. Connected automobiles generate data depending on criteria such as speed, engine state, and distance travelled.

Regional Outlook

Region-wise, the Automotive Data Management Market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment garnered the revenue share in the automotive data management market in 2021. It is due to the factors such as the existence of key market vendors, considerable disposable incomes, the need for new automobiles, and the increasing adoption of modern technology. Moreover, advances in U.S. traffic legislation that let autonomous vehicles interact on roads and highways have led to a surge in the testing and usage of self-driving vehicles, which is likely to drive the need for automotive data management in the area.

The Cardinal Matrix - Automotive Data Management Market Competition Analysis



The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation and Amazon Web Services, Inc. are the forerunners in the Automotive Data Management Market. Companies such as SAP SE, IBM Corporation, Azuga, Inc. are some of the key innovators in Automotive Data Management Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Sibros Technologies Inc., Azuga, Inc. (Bridgestone Corporation), Microsoft Corporation, SAP SE, IBM Corporation, Amazon Web Services, Inc. (Amazon.com, Inc.), Otonomo Technologies Ltd., Agnik LLC, Procon Analytics, LLC and Xevo, Inc. (Lear Corporation)

Strategies Deployed in Automotive Data Management Market

Partnerships, Collaborations and Agreements:

  • Oct-2022: Microsoft joined hands with Mercedes-Benz, which offers financing, leasing, car subscription and car rental, and fleet management. Together, the companies aimed to combine the physical and digital worlds to propel value creation. Moreover, Mercedes-Benz can simulate and refine manufacturing procedures infinitely in the Microsoft Cloud before getting them to the shop floor to improve productivity and reduce their ecological effect amid ongoing change and uncertainty.
  • Oct-2022: SAP came into a partnership with Otonomo, a leading platform, and marketplace for vehicle data. Through this partnership, the companies aimed to combine its smart mobility data platform with sap digital vehicle hub. Moreover, combining the otonomo smart mobility data platform with sap digital vehicle hub aids companies to more effectively handle connected vehicle data across their vehicle fleets.
  • Oct-2022: AWS joined hands with BMW, the world’s foremost premium manufacturer of automobiles and motorcycles. Through this collaboration, the companies aimed to provide a solution that contains BMW vehicle signals and fleet intelligence data, then securely procedures and route the data in the cloud. Moreover, AWS and BMW Group are eager to make the concept of software-defined transportation an existence and to improve the abilities of vehicles on the road.
  • Aug-2022: Sibros came into a partnership with Google Cloud Platform, a platform offered by Google. Together, the companies aimed to bring flexible and intelligent connected vehicle-to-cloud solutions to automakers across the world. Moroever, Sibros’ connected vehicle solution would be available on Google Cloud, enhanced with a variety of Google apps, cloud, and automotive services to assist automakers to reinvent the connected mobility experience.
  • Aug-2022: SAP joined hands with Capgemini, a multinational information technology services and consulting company. Together, the companies aimed to boost the automotive industry’s journey forward in sustainability. Additionally, Capgemini and SAP would deliver cloud products and services to sustain sustainability transformation in technology, strategy, and business model change. Moreover, the collaboration would help automotive companies identify the business importance of sustainability and inject sustainability management into products and services across their supply chains.
  • Jul-2022: Azuga formed a partnership with CerebrumX, an AI-Powered Connected Vehicle Data Platform. This partnership aimed to utilize the ability of connected vehicle data to optimize fleet management with real-time, actionable, and precise insights. Moreover, this collaboration with Azuga would reinforce Azuga's fleet tracking platform with CerebrumX's artificial intelligence-powered Augmented Deep Learning Platform (ADLP) providing implanted vehicle data and cloud-based telematic application programming interface (API) s.
  • Mar-2022: Sibros joined hands with ACTIA, a foremost player in the manufacture, design, and diagnostics of electronic embedded systems. Through this collaboration, the companies aimed to combine Sibros’ OTA firmware products with the ACU6, Sibros have assembled a powerful combination to help consumers introduce new connected vehicle features, decrease time-to-market and complete global security, safety, and data privacy conditions right out-of-the-box.
  • Mar-2022: Otonomo joined hands with Henshin along with wefox. Through this collaboration, the companies aimed to develop rich, actionable vehicle data sets to force innovation and create additional value for enterprises delivering rental, insurance, and leasing services to fleet vehicle operators. Moreover, wefox also declared it would be the first to market with new insurance products enabled by the joint platform.
  • Feb-2022: Sibros Technologies formed a partnership with Pricol Limited, automotive components, and precision-engineered products. This partnership aimed to provide deep connected vehicle solutions in the ASEAN and Indian markets. Moreover, Sibros’ connected all-in-one platform would complete Pricol’s offering of products on Driver Information Systems (DIS) and Telematics to deliver end-to-end solutions to the OEMs.
  • Jan-2022: Microsoft joined hands with Annata, a Global independent solution provider. This collaboration aimed to drive the conversion of distribution and retail and to allow new mobility services. Moreover, Annata’s customer relationships and growing offering of abilities in Annata 365 integrated with the strength and scale of the Microsoft Cloud would help provide the solutions the industry needs at scale.
  • Jan-2022: SAP formed a partnership with Mahindra & Mahindra, the world’s biggest tractor division. Through this partnership, SAP would allow Mahindra & Mahindra to successfully advance their technology landscape and improve their general procedures by relocating SAP to a safe managed cloud environment whilst driving to a microservices-enabled open stack architecture facilitated by utilizing SAP Business Technology Platform.
  • Jan-2022: Amazon teamed up with Stellantis, a multinational automotive manufacturing corporation. Together, the companies aimed to develop an offering of software-based products and services that seamlessly combine with consumers’ digital lives and add value over time via regular over-the-air (OTA) software updates.
  • Jan-2022: Otonomo came into a partnership with AUDI AG, a German automotive manufacturer of luxury vehicles. Through this partnership, Audi will would deliver Otonomo with data points from Audi-connected cars, ranging from odometer readings to crash information, including crash location and severity. Moreover, this partnership is a crucial option that would authorize Otonomo to cooperate on innovative technologies and upcoming services.
  • Jan-2022: Otonomo Technologies partnered with NextBillion.ai, a provider of an enterprise Map Data and AI platform. This partnership would drive innovation and time to market for products and services of mobility companies across the globe. Additionally, NextBillion.ai would represent a step forward in the mobility intelligence solutions available to fleets, smart cities, EV providers, and others.
  • Dec-2021: Otonomo partnered with NXP Semiconductors, a Dutch semiconductor designer and manufacturer. This partnership aimed to drive the time-to-value for the data developed at the vehicle edge. Moreover, the partnership provides alignment and business continuity between NXP’s S32G vehicle network processors at the vehicle edge and the Otonomo Mobility Intelligence Platform in the cloud, to deliver a smooth, safe infrastructure for transmitting data from the vehicle to the cloud.
  • Aug-2021: Azuga formed a partnership with ServiceTrade, a software-as-a-service platform that handles job scheduling. Together, the companies aimed to assist commercial contractors to enhance Service and simplify procedures. Moreover, the ServiceTrade combination delivers a wide range of advantages to fire protection contractors, commercial building service contractors, mechanical and commercial HVAC businesses, etc.
  • Aug-2021: Microsoft teamed up with Arrival, a producer of multi-category commercial electric vehicles. Through this collaboration, the companies aimed to jointly develop an automotive open data platform. Additionally, Microsoft Azure would allow advanced telemetry, and vehicle and fleet data management within vehicle fleets.
  • Jul-2021: Otonomo formed a partnership with Mercedes-Benz, a German luxury and commercial vehicle. Through this partnership, Otonomo would create fleet data available across 25 countries throughout Europe to fleet management companies and operators, such as delivery companies, service providers, car rental businesses, and others, so that they can achieve immediate access to connected vehicle data and enhance their productivity and decrease expenses. Moroever, Otonomo looks forward to fleets across Europe utilizing vehicle data from Otonomo to operate with decreased IT burden, smarter routing, safer driving, and fuel savings for fleets across Europe.
  • Jun-2021: Otonomo teamed up with Amazon Web Services, a subsidiary of Amazon. This collaboration would further promote the transformation of the mobility ecosystem and speed up transportation services for all. Additionally, together, AWS and Otonomo would provide a solution for the automotive industry to completely utilize the value of connected vehicle data.
  • Feb-2020: SAP teamed up with proaxia automotive solutions. This collaboration aimed to benefit consumers in the vehicle and heavy equipment dealer enterprise along with the workshop service business. Moreover, the partnership with proaxia would accelerate SAP's consumer journey toward an intelligent business in the automotive retail industry for dealerships.

Product Launches and Product Expansions:

  • Sep-2022: Sibros launched recallsdata.com, the first software-related recalls analytics dashboard. Recallsdata.com was developed in search of its vision of a net zero software flaws future in the next 10 years, thus eradicating all software-related vehicle recalls by 2032. Moreover, Vehicle recalls are a resumed safety, cost- and time-intensive challenge in the automotive industry.
  • Dec-2021: AWS launched AWS FleetWise along with AWS Automotive. The AWS FleetWise is a new service that creates it easier for automakers to gather and retrieve sensor and telemetry data from their vehicle fleets whereas AWS Automotive, a wider, industry-specific initiative that provides together a range of the company’s products under a single umbrella, equivalent to AWS’s other industry solutions such as AWS for Industrial.
  • Mar-2021: Azuga introduced SafetyIQ, a new Software as a Service solution for insurance firms and commercial auto fleet owners and managers. The safetyIQ allows owner/manager consumers to decrease expenses and enhance road safety.

Acquisitions and Mergers:

  • Apr-2022: Otonomo completed the acquisition Floow, a United Kingdom-based SaaS provider. With this acquisition, Floow’s established offering of connected insurance customers and strategic partnerships with Otonomo’s connected car platform, Otonomo believe that they are now even better positioned to deliver prominent intelligent and connected solutions to the international data mobility market.
  • Jul-2021: IBM took over Bluetab, an IT Services boutique serving large corporations. With this acquisition, the Blue tab would accelerate migration to the cloud and help customers to recognize even more importance of their mission-critical data.
  • Mar-2021: Azuga completed the acquisition of Mobility, which harmonizes, enriches, and analyzes connected vehicle data. With this acquisition, Azuga would create a new SaaS platform to boost the advantages and insights of telematics, AI, video, and vehicle data delivers to Carriers, MGAs, Brokers, and other insurance suppliers. Moreover, Mobikit offers data infrastructure for connected vehicles, and let's harmonize, enrich, and analyze connected vehicle data.
  • Dec-2020: IBM completed the acquisition of Instana, a German-American software firm. With this acquisition, IBM would deliver industry-leading, AI-powered automation abilities to handle the complexity of modern applications that travel hybrid cloud landscapes.

Scope of the Study

By Component

  • Software
  • Services

By Data Type

  • Structured
  • Unstructured

By Application

  • Driver & User Behavior Analysis
  • Safety & Security Management
  • Predictive Maintenance
  • Warranty Analytics
  • Dealer Performance Analysis

By Deployment Type

  • Cloud
  • On-premise

By Vehicle Type

  • Non-autonomous
  • Autonomous

By Geography

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

  • Sibros Technologies Inc.
  • Azuga, Inc. (Bridgestone Corporation)
  • Microsoft Corporation
  • SAP SE
  • IBM Corporation
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • Otonomo Technologies Ltd.
  • Agnik LLC
  • Procon Analytics, LLC.
  • Xevo, Inc. (Lear Corporation)

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Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Automotive Data Management Market, by Component
1.4.2 Global Automotive Data Management Market, by Data Type
1.4.3 Global Automotive Data Management Market, by Application
1.4.4 Global Automotive Data Management Market, by Deployment Type
1.4.5 Global Automotive Data Management Market, by Vehicle Type
1.4.6 Global Automotive Data Management Market, by Geography
1.5 Research Methodology
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition & Scenarios
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 The Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.3.2 Key Strategic Move: (Partnerships, Collaborations, and Agreements: 2019, Jan - 2022, Oct) Leading Players
Chapter 4. Global Automotive Data Management Market by Component
4.1 Global Software Market by Region
4.2 Global Services Market by Region
Chapter 5. Global Automotive Data Management Market by Data Type
5.1 Global Structured Market by Region
5.2 Global Unstructured Market by Region
Chapter 6. Global Automotive Data Management Market by Application
6.1 Global Driver & User Behavior Analysis Market by Region
6.2 Global Safety & Security Management Market by Region
6.3 Global Predictive Maintenance Market by Region
6.4 Global Warranty Analytics Market by Region
6.5 Global Dealer Performance Analysis Market by Region
Chapter 7. Global Automotive Data Management Market by Deployment Type
7.1 Global Cloud Market by Region
7.2 Global On-premise Market by Region
Chapter 8. Global Automotive Data Management Market by Vehicle Type
8.1 Global Non-autonomous Market by Region
8.2 Global Autonomous Market by Region
Chapter 9. Global Automotive Data Management Market by Region
9.1 North America Automotive Data Management Market
9.1.1 North America Automotive Data Management Market by Component
9.1.1.1 North America Software Market by Country
9.1.1.2 North America Services Market by Country
9.1.2 North America Automotive Data Management Market by Data Type
9.1.2.1 North America Structured Market by Country
9.1.2.2 North America Unstructured Market by Country
9.1.3 North America Automotive Data Management Market by Application
9.1.3.1 North America Driver & User Behavior Analysis Market by Country
9.1.3.2 North America Safety & Security Management Market by Country
9.1.3.3 North America Predictive Maintenance Market by Country
9.1.3.4 North America Warranty Analytics Market by Country
9.1.3.5 North America Dealer Performance Analysis Market by Country
9.1.4 North America Automotive Data Management Market by Deployment Type
9.1.4.1 North America Cloud Market by Country
9.1.4.2 North America On-premise Market by Country
9.1.5 North America Automotive Data Management Market by Vehicle Type
9.1.5.1 North America Non-autonomous Market by Country
9.1.5.2 North America Autonomous Market by Country
9.1.6 North America Automotive Data Management Market by Country
9.1.6.1 US Automotive Data Management Market
9.1.6.1.1 US Automotive Data Management Market by Component
9.1.6.1.2 US Automotive Data Management Market by Data Type
9.1.6.1.3 US Automotive Data Management Market by Application
9.1.6.1.4 US Automotive Data Management Market by Deployment Type
9.1.6.1.5 US Automotive Data Management Market by Vehicle Type
9.1.6.2 Canada Automotive Data Management Market
9.1.6.2.1 Canada Automotive Data Management Market by Component
9.1.6.2.2 Canada Automotive Data Management Market by Data Type
9.1.6.2.3 Canada Automotive Data Management Market by Application
9.1.6.2.4 Canada Automotive Data Management Market by Deployment Type
9.1.6.2.5 Canada Automotive Data Management Market by Vehicle Type
9.1.6.3 Mexico Automotive Data Management Market
9.1.6.3.1 Mexico Automotive Data Management Market by Component
9.1.6.3.2 Mexico Automotive Data Management Market by Data Type
9.1.6.3.3 Mexico Automotive Data Management Market by Application
9.1.6.3.4 Mexico Automotive Data Management Market by Deployment Type
9.1.6.3.5 Mexico Automotive Data Management Market by Vehicle Type
9.1.6.4 Rest of North America Automotive Data Management Market
9.1.6.4.1 Rest of North America Automotive Data Management Market by Component
9.1.6.4.2 Rest of North America Automotive Data Management Market by Data Type
9.1.6.4.3 Rest of North America Automotive Data Management Market by Application
9.1.6.4.4 Rest of North America Automotive Data Management Market by Deployment Type
9.1.6.4.5 Rest of North America Automotive Data Management Market by Vehicle Type
9.2 Europe Automotive Data Management Market
9.2.1 Europe Automotive Data Management Market by Component
9.2.1.1 Europe Software Market by Country
9.2.1.2 Europe Services Market by Country
9.2.2 Europe Automotive Data Management Market by Data Type
9.2.2.1 Europe Structured Market by Country
9.2.2.2 Europe Unstructured Market by Country
9.2.3 Europe Automotive Data Management Market by Application
9.2.3.1 Europe Driver & User Behavior Analysis Market by Country
9.2.3.2 Europe Safety & Security Management Market by Country
9.2.3.3 Europe Predictive Maintenance Market by Country
9.2.3.4 Europe Warranty Analytics Market by Country
9.2.3.5 Europe Dealer Performance Analysis Market by Country
9.2.4 Europe Automotive Data Management Market by Deployment Type
9.2.4.1 Europe Cloud Market by Country
9.2.4.2 Europe On-premise Market by Country
9.2.5 Europe Automotive Data Management Market by Vehicle Type
9.2.5.1 Europe Non-autonomous Market by Country
9.2.5.2 Europe Autonomous Market by Country
9.2.6 Europe Automotive Data Management Market by Country
9.2.6.1 Germany Automotive Data Management Market
9.2.6.1.1 Germany Automotive Data Management Market by Component
9.2.6.1.2 Germany Automotive Data Management Market by Data Type
9.2.6.1.3 Germany Automotive Data Management Market by Application
9.2.6.1.4 Germany Automotive Data Management Market by Deployment Type
9.2.6.1.5 Germany Automotive Data Management Market by Vehicle Type
9.2.6.2 UK Automotive Data Management Market
9.2.6.2.1 UK Automotive Data Management Market by Component
9.2.6.2.2 UK Automotive Data Management Market by Data Type
9.2.6.2.3 UK Automotive Data Management Market by Application
9.2.6.2.4 UK Automotive Data Management Market by Deployment Type
9.2.6.2.5 UK Automotive Data Management Market by Vehicle Type
9.2.6.3 France Automotive Data Management Market
9.2.6.3.1 France Automotive Data Management Market by Component
9.2.6.3.2 France Automotive Data Management Market by Data Type
9.2.6.3.3 France Automotive Data Management Market by Application
9.2.6.3.4 France Automotive Data Management Market by Deployment Type
9.2.6.3.5 France Automotive Data Management Market by Vehicle Type
9.2.6.4 Russia Automotive Data Management Market
9.2.6.4.1 Russia Automotive Data Management Market by Component
9.2.6.4.2 Russia Automotive Data Management Market by Data Type
9.2.6.4.3 Russia Automotive Data Management Market by Application
9.2.6.4.4 Russia Automotive Data Management Market by Deployment Type
9.2.6.4.5 Russia Automotive Data Management Market by Vehicle Type
9.2.6.5 Spain Automotive Data Management Market
9.2.6.5.1 Spain Automotive Data Management Market by Component
9.2.6.5.2 Spain Automotive Data Management Market by Data Type
9.2.6.5.3 Spain Automotive Data Management Market by Application
9.2.6.5.4 Spain Automotive Data Management Market by Deployment Type
9.2.6.5.5 Spain Automotive Data Management Market by Vehicle Type
9.2.6.6 Italy Automotive Data Management Market
9.2.6.6.1 Italy Automotive Data Management Market by Component
9.2.6.6.2 Italy Automotive Data Management Market by Data Type
9.2.6.6.3 Italy Automotive Data Management Market by Application
9.2.6.6.4 Italy Automotive Data Management Market by Deployment Type
9.2.6.6.5 Italy Automotive Data Management Market by Vehicle Type
9.2.6.7 Rest of Europe Automotive Data Management Market
9.2.6.7.1 Rest of Europe Automotive Data Management Market by Component
9.2.6.7.2 Rest of Europe Automotive Data Management Market by Data Type
9.2.6.7.3 Rest of Europe Automotive Data Management Market by Application
9.2.6.7.4 Rest of Europe Automotive Data Management Market by Deployment Type
9.2.6.7.5 Rest of Europe Automotive Data Management Market by Vehicle Type
9.3 Asia Pacific Automotive Data Management Market
9.3.1 Asia Pacific Automotive Data Management Market by Component
9.3.1.1 Asia Pacific Software Market by Country
9.3.1.2 Asia Pacific Services Market by Country
9.3.2 Asia Pacific Automotive Data Management Market by Data Type
9.3.2.1 Asia Pacific Structured Market by Country
9.3.2.2 Asia Pacific Unstructured Market by Country
9.3.3 Asia Pacific Automotive Data Management Market by Application
9.3.3.1 Asia Pacific Driver & User Behavior Analysis Market by Country
9.3.3.2 Asia Pacific Safety & Security Management Market by Country
9.3.3.3 Asia Pacific Predictive Maintenance Market by Country
9.3.3.4 Asia Pacific Warranty Analytics Market by Country
9.3.3.5 Asia Pacific Dealer Performance Analysis Market by Country
9.3.4 Asia Pacific Automotive Data Management Market by Deployment Type
9.3.4.1 Asia Pacific Cloud Market by Country
9.3.4.2 Asia Pacific On-premise Market by Country
9.3.5 Asia Pacific Automotive Data Management Market by Vehicle Type
9.3.5.1 Asia Pacific Non-autonomous Market by Country
9.3.5.2 Asia Pacific Autonomous Market by Country
9.3.6 Asia Pacific Automotive Data Management Market by Country
9.3.6.1 China Automotive Data Management Market
9.3.6.1.1 China Automotive Data Management Market by Component
9.3.6.1.2 China Automotive Data Management Market by Data Type
9.3.6.1.3 China Automotive Data Management Market by Application
9.3.6.1.4 China Automotive Data Management Market by Deployment Type
9.3.6.1.5 China Automotive Data Management Market by Vehicle Type
9.3.6.2 Japan Automotive Data Management Market
9.3.6.2.1 Japan Automotive Data Management Market by Component
9.3.6.2.2 Japan Automotive Data Management Market by Data Type
9.3.6.2.3 Japan Automotive Data Management Market by Application
9.3.6.2.4 Japan Automotive Data Management Market by Deployment Type
9.3.6.2.5 Japan Automotive Data Management Market by Vehicle Type
9.3.6.3 India Automotive Data Management Market
9.3.6.3.1 India Automotive Data Management Market by Component
9.3.6.3.2 India Automotive Data Management Market by Data Type
9.3.6.3.3 India Automotive Data Management Market by Application
9.3.6.3.4 India Automotive Data Management Market by Deployment Type
9.3.6.3.5 India Automotive Data Management Market by Vehicle Type
9.3.6.4 South Korea Automotive Data Management Market
9.3.6.4.1 South Korea Automotive Data Management Market by Component
9.3.6.4.2 South Korea Automotive Data Management Market by Data Type
9.3.6.4.3 South Korea Automotive Data Management Market by Application
9.3.6.4.4 South Korea Automotive Data Management Market by Deployment Type
9.3.6.4.5 South Korea Automotive Data Management Market by Vehicle Type
9.3.6.5 Singapore Automotive Data Management Market
9.3.6.5.1 Singapore Automotive Data Management Market by Component
9.3.6.5.2 Singapore Automotive Data Management Market by Data Type
9.3.6.5.3 Singapore Automotive Data Management Market by Application
9.3.6.5.4 Singapore Automotive Data Management Market by Deployment Type
9.3.6.5.5 Singapore Automotive Data Management Market by Vehicle Type
9.3.6.6 Malaysia Automotive Data Management Market
9.3.6.6.1 Malaysia Automotive Data Management Market by Component
9.3.6.6.2 Malaysia Automotive Data Management Market by Data Type
9.3.6.6.3 Malaysia Automotive Data Management Market by Application
9.3.6.6.4 Malaysia Automotive Data Management Market by Deployment Type
9.3.6.6.5 Malaysia Automotive Data Management Market by Vehicle Type
9.3.6.7 Rest of Asia Pacific Automotive Data Management Market
9.3.6.7.1 Rest of Asia Pacific Automotive Data Management Market by Component
9.3.6.7.2 Rest of Asia Pacific Automotive Data Management Market by Data Type
9.3.6.7.3 Rest of Asia Pacific Automotive Data Management Market by Application
9.3.6.7.4 Rest of Asia Pacific Automotive Data Management Market by Deployment Type
9.3.6.7.5 Rest of Asia Pacific Automotive Data Management Market by Vehicle Type
9.4 LAMEA Automotive Data Management Market
9.4.1 LAMEA Automotive Data Management Market by Component
9.4.1.1 LAMEA Software Market by Country
9.4.1.2 LAMEA Services Market by Country
9.4.2 LAMEA Automotive Data Management Market by Data Type
9.4.2.1 LAMEA Structured Market by Country
9.4.2.2 LAMEA Unstructured Market by Country
9.4.3 LAMEA Automotive Data Management Market by Application
9.4.3.1 LAMEA Driver & User Behavior Analysis Market by Country
9.4.3.2 LAMEA Safety & Security Management Market by Country
9.4.3.3 LAMEA Predictive Maintenance Market by Country
9.4.3.4 LAMEA Warranty Analytics Market by Country
9.4.3.5 LAMEA Dealer Performance Analysis Market by Country
9.4.4 LAMEA Automotive Data Management Market by Deployment Type
9.4.4.1 LAMEA Cloud Market by Country
9.4.4.2 LAMEA On-premise Market by Country
9.4.5 LAMEA Automotive Data Management Market by Vehicle Type
9.4.5.1 LAMEA Non-autonomous Market by Country
9.4.5.2 LAMEA Autonomous Market by Country
9.4.6 LAMEA Automotive Data Management Market by Country
9.4.6.1 Brazil Automotive Data Management Market
9.4.6.1.1 Brazil Automotive Data Management Market by Component
9.4.6.1.2 Brazil Automotive Data Management Market by Data Type
9.4.6.1.3 Brazil Automotive Data Management Market by Application
9.4.6.1.4 Brazil Automotive Data Management Market by Deployment Type
9.4.6.1.5 Brazil Automotive Data Management Market by Vehicle Type
9.4.6.2 Argentina Automotive Data Management Market
9.4.6.2.1 Argentina Automotive Data Management Market by Component
9.4.6.2.2 Argentina Automotive Data Management Market by Data Type
9.4.6.2.3 Argentina Automotive Data Management Market by Application
9.4.6.2.4 Argentina Automotive Data Management Market by Deployment Type
9.4.6.2.5 Argentina Automotive Data Management Market by Vehicle Type
9.4.6.3 UAE Automotive Data Management Market
9.4.6.3.1 UAE Automotive Data Management Market by Component
9.4.6.3.2 UAE Automotive Data Management Market by Data Type
9.4.6.3.3 UAE Automotive Data Management Market by Application
9.4.6.3.4 UAE Automotive Data Management Market by Deployment Type
9.4.6.3.5 UAE Automotive Data Management Market by Vehicle Type
9.4.6.4 Saudi Arabia Automotive Data Management Market
9.4.6.4.1 Saudi Arabia Automotive Data Management Market by Component
9.4.6.4.2 Saudi Arabia Automotive Data Management Market by Data Type
9.4.6.4.3 Saudi Arabia Automotive Data Management Market by Application
9.4.6.4.4 Saudi Arabia Automotive Data Management Market by Deployment Type
9.4.6.4.5 Saudi Arabia Automotive Data Management Market by Vehicle Type
9.4.6.5 South Africa Automotive Data Management Market
9.4.6.5.1 South Africa Automotive Data Management Market by Component
9.4.6.5.2 South Africa Automotive Data Management Market by Data Type
9.4.6.5.3 South Africa Automotive Data Management Market by Application
9.4.6.5.4 South Africa Automotive Data Management Market by Deployment Type
9.4.6.5.5 South Africa Automotive Data Management Market by Vehicle Type
9.4.6.6 Nigeria Automotive Data Management Market
9.4.6.6.1 Nigeria Automotive Data Management Market by Component
9.4.6.6.2 Nigeria Automotive Data Management Market by Data Type
9.4.6.6.3 Nigeria Automotive Data Management Market by Application
9.4.6.6.4 Nigeria Automotive Data Management Market by Deployment Type
9.4.6.6.5 Nigeria Automotive Data Management Market by Vehicle Type
9.4.6.7 Rest of LAMEA Automotive Data Management Market
9.4.6.7.1 Rest of LAMEA Automotive Data Management Market by Component
9.4.6.7.2 Rest of LAMEA Automotive Data Management Market by Data Type
9.4.6.7.3 Rest of LAMEA Automotive Data Management Market by Application
9.4.6.7.4 Rest of LAMEA Automotive Data Management Market by Deployment Type
9.4.6.7.5 Rest of LAMEA Automotive Data Management Market by Vehicle Type
Chapter 10. Company Profiles
10.1 IBM Corporation
10.1.1 Company Overview
10.1.2 Financial Analysis
10.1.3 Regional & Segmental Analysis
10.1.4 Research & Development Expenses
10.1.5 Recent Strategies and Developments
10.1.5.1 Acquisition and Mergers
10.1.6 SWOT Analysis
10.2 Amazon Web Services, Inc. (Amazon.com, Inc.)
10.2.1 Company Overview
10.2.2 Financial Analysis
10.2.3 Segmental Analysis
10.2.4 Recent Strategies and Developments
10.2.4.1 Partnerships, Collaborations, and Agreements
10.2.4.2 Product Launches and Product Expansions
10.2.5 SWOT Analysis
10.3 Microsoft Corporation
10.3.1 Company Overview
10.3.2 Financial Analysis
10.3.3 Segmental and Regional Analysis
10.3.4 Research & Development Expenses
10.3.5 Recent Strategies and Developments
10.3.5.1 Partnerships, Collaborations, and Agreements
10.3.6 SWOT Analysis
10.4 SAP SE
10.4.1 Company Overview
10.4.2 Financial Analysis
10.4.3 Segmental and Regional Analysis
10.4.4 Research & Development Expense
10.4.5 Recent Strategies and Developments
10.4.5.1 Partnerships, Collaborations, and Agreements
10.4.6 SWOT Analysis
10.5 Azuga, Inc. (Bridgestone Corporation)
10.5.1 Company Overview
10.5.2 Financial Analysis
10.5.3 Segmental Analysis
10.5.4 Research & Development Expenses
10.5.5 Recent Strategies and Developments
10.5.5.1 Partnerships, Collaborations, and Agreements
10.5.5.2 Product Launches and Product Expansions
10.5.5.3 Acquisition and Mergers
10.6 Otonomo Technologies Ltd.
10.6.1 Company Overview
10.6.2 Financial Analysis
10.6.3 Regional Analysis
10.6.4 Research & Development Expenses
10.6.5 Recent Strategies and Developments
10.6.5.1 Partnerships, Collaborations, and Agreements
10.6.5.2 Acquisition and Mergers
10.7 Xevo, Inc. (Lear Corporation)
10.7.1 Company Overview
10.7.2 Financial Analysis
10.7.3 Segmental and Regional Analysis
10.7.4 Recent Strategies and Developments
10.7.4.1 Partnerships, Collaborations, and Agreements
10.8 Sibros Technologies, Inc.
10.8.1 Company Overview
10.8.2 Recent Strategies and Developments
10.8.2.1 Partnerships, Collaborations, and Agreements
10.8.2.2 Product Launches and Product Expansions
10.9 Agnik LLC
10.9.1 Company Overview
10.10. Procon Analytics, LLC.
10.10.1 Company Overview

Companies Mentioned

  • Sibros Technologies Inc.
  • Azuga, Inc. (Bridgestone Corporation)
  • Microsoft Corporation
  • SAP SE
  • IBM Corporation
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • Otonomo Technologies Ltd.
  • Agnik LLC
  • Procon Analytics, LLC.
  • Xevo, Inc. (Lear Corporation)

Methodology

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