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Automotive Data Management Market worth over $4 Bn by 2028

  • Published Date: April 6, 2022

Automotive Data Management Market size is set to cross USD 4 billion by 2028, according to a new research report by Global Market Insights Inc.

Increasing investments in autonomous vehicle technology is fueling the industry growth. Various automotive companies are extensively investing in advanced vehicle technologies. For instance, in July 2021, Ghost raised USD 100 million in series D round. The investment was led by Sutter Hill Ventures. Through this investment, the company developed advanced self-driving and crash prevention technology. The major automotive data management service providers are focusing on developing advanced & integrated automotive data management solutions.

Growing adoption of cloud-based services in the automotive sector

The automotive data management market from service segment is anticipated to observe nearly 25% CAGR through 2028. This growth is credited to the increasing demand for customized value-added data management services in various end-users such as fleet owners, automotive dealers, OEMs, and others. Automotive companies are providing different types of data management services such as data quality services, data migration services, data modeling services, cloud computing services, and others. Automotive data management services help in improving the vehicle performance and provide enhanced customer experiences.

Global Automotive Data Management Market Size By Region

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Changing consumer preferences to adopt connected vehicles

The unstructured data segment held around 75% of the market share in 2021 owing to growing adoption of connected and autonomous vehicles. Autonomous vehicles collect a huge amount of unstructured data.

Moreover, automotive market players are increasingly adopting cloud technology to store vehicle unstructured data in cloud. As unstructured data is helpful in the further development of autonomous vehicles. Some automotive companies are using unstructured data with AI structuring systems to understand the driver behavior and vehicle performance.

Browse key industry insights spread across 382 pages with 479 market data tables and 39 figures & charts from the report, “Automotive Data Management Market Size By Component (Software [Data Security, Data Integration, Data Migration, Data Quality], Service [Professional Service, Managed Service]), By Data Type (Unstructured, Semi-structured and Structured), By Vehicle Type (Autonomous, Non-autonomous), By Deployment (On-premise, Cloud), By Application (Predictive Maintenance, Warranty Analytics, Safety and Security Management, Driver and User Behavior Analytics, Dealer Performance Analysis), COVID-19 Impact Analysis, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2022 – 2028”, in detail along with the table of contents:


Increasing focus on vehicle & road safety

The automotive data management market from autonomous vehicle segment is projected to expand at over 25% gains till 2028. Growing number of road fatalities, and vehicle manufacturers are deploying advanced driver assistance and autonomous driving systems are boosting the market growth. For instance, in October 2020, Daimler Truck Group signed a strategic partnership with Waymo, LLC for the development of autonomous commercial trucks. Through this partnership, Daimler Truck Group leveraged Waymo’s expertise in the autonomous driving technology. This helped the company to support the deployment of autonomous SAE L4 technology.

Rising usage of advanced technology-based automotive data management solutions

The on-premise segment is poised to register a growth rate of about20% through 2028 owing to the growing acceptance of advanced telematic solutions. Automotive participants in the region are collaborating with enterprises operating in the market to deploy telematics solutions.

Growing adoption of data analytics tools in the automotive sector

The predictive maintenance segment accounted for 20% of the automotive data management market share in 2021 driven by growing need to increase vehicle quality & productivity. Predictive maintenance helps in predicting & identifying the major vehicle issues. It offers several advanced features such as end-to-end service operations, improved vehicle performance, cost saving, and improved reliability. Predictive maintenance applications provide roadside assistance, track vehicle health, enhanced security, and others. Several automotive firms are investing to expand their predictive maintenance capabilities

Rising investments in connected vehicles across Asia Pacific

Asia Pacific automotive data management market size is expected to generate more than USD 900 million revenue by 2028. This growth is attributed to the supportive government initiatives by different countries to safeguard mobility, thereby boosting the demand for autonomous vehicles in the region. Furthermore, countries, including China and South Korea, are developing urban air Mobility-as-a-Service (MaaS) to connect the entire infrastructure.

Asia Pacific is a highly lucrative market for the adoption of IoT technologies due to numerous government initiatives for large-scale digitalization of urban infrastructure in countries including China, South Korea, and India. China is planning to transform its automotive sector with the help of advanced technologies, such as 5G, cloud computing, big data, and IoT, creating ample growth opportunities.

Leading industry players are focusing on developing advanced solutions to gain a competitive advantage

Key players operating in the automotive data management market include Acerta Analytics Solutions, Inc., Agnik, LLC, Amazon Web Service, Inc., AMO Foundation, Amodo D.o.o, Caruso GmbH, ETL Solutions Limited, HEAVY.AI, IBM Corporation, Intellias, National Instruments Corporation, NetApp, Inc., Otonomo Technologies Ltd., SAP SE, Sibros Technologies, Inc., Teradata Corporation, Vinli, Inc., and WEJO Limited. The companies are developing more advanced automotive data management solutions to meet customers’ demand.

Authors: Preeti Wadhwani, Smriti Loomba