Application of Data Management Capability Maturity Assessment Model in the Automotive Industry

DOI: https://doi.org/10.62517/jcte.202406105

Author(s)

Sisi Chu*, Jian Ma, Yingzi Wang

Affiliation(s)

China Automotive Technology & Research Center Co. Ltd, Tianjin, China *Corresponding Author

Abstract

In the era of digital economy, data has become an important production factor and strategic asset. Data governance in the automotive industry generally faces pain points such as decentralized construction of business data, multi head management of data resources, and incomplete management of data lifecycle. Data management capability maturity assessment model provides important guidance for enterprises on how to better enhance their data management capabilities by defining eight capability domains: data model, data standards, data quality, and data security. By using the data management capability maturity assessment model, this paper analyses the data characteristics, business needs and development trends of the automotive industry, focuses on data interconnection, compliance sharing, value mining and agile services, starting from four aspects: organization, management, technology, and execution. It forms a data management solution and architecture system with the characteristics of the automotive industry, including multiple fields such as data, algorithms, models, and applications, promoting data management capabilities to become a new growth point and new development momentum for enterprises' digital transformation and building competitive advantages. At the same time, this paper looks forward to the future trend of automotive big data governance and proposes that building a big data governance system in the automotive industry characterized by "integration, collaboration, intelligence, security, and openness" will become the necessary path.

Keywords

Data Management Capability; Dcmm, Automotive Industry; Data Governance; Data Element

References

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