What Are the Best Tips for Data Asset Management?

The definition of "data asset management" in foreign countries is: Data asset management (DAM) is a set of business functions for planning, controlling and providing data and information assets, including the development, execution and supervision of relevant data plans, policies, Programs, projects, processes, methods and procedures to control, protect, deliver and increase the value of data assets.

Data asset management

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The definition of "data asset management" in foreign countries is: Data asset management (DAM) is a set of business functions for planning, controlling and providing data and information assets, including the development, execution and supervision of relevant data plans, policies, Programs, projects, processes, methods and procedures to control, protect, deliver and increase the value of data assets.

The term "data asset management" was officially proposed for the first time in China by the DAMS (China Data Asset Management Summit) Organizing Committee.

The concept of data management has been proposed for nearly 40 years since the 1980s, and the term of data governance has been used for nearly 20 years. The proposal of data asset management is basically a matter of the last 5 years. China Data Asset Management Summit Is defined as a management process for data management, data governance, and data assetization.

Chinese name

Data asset management

Foreign name

Data asset management

The term "data asset management" was officially proposed for the first time in China by the DAMS (China Data Asset Management Summit) Organizing Committee. The first "China Data Asset Management Summit" was directed by the Shanghai Economic and Information Commission, hosted by the Shanghai Cloud Computing Industry Promotion Center, and co-organized by Xinju Network and 51CTO. The aim is to build a platform for data asset management ideas to collide and communicate, and share leading data asset management concepts and practical experience with colleagues in the industry. Committed to making the "China Data Asset Management Summit" a benchmarking summit in the field of data asset management and promoting the development of China's data asset management industry.

Assets are valuable assets controlled by individuals or organizations. Enterprise assets help achieve the goals of the enterprise. The data and the information generated by the data are now recognized as corporate assets.

At present, without high-quality data, it is difficult for companies to still run efficiently. Today, businesses rely on their data assets to make smarter and more effective decisions. Market leaders are using data assets to gain competitive advantage through rich customer profiles, innovative use of information, and efficient operations. Enterprises use data assets to provide better products and services, reduce costs, and control risks. With the growing demand for data and the increasing dependence on data, people can more and more clearly assess the business value of data assets.

Every enterprise needs to effectively manage its increasingly important data. Through the cooperation of business leaders and technical experts, the data asset management function can effectively provide and control data and information assets.

With the maturity and development of the data management industry abroad, data asset management has been widely studied and summarized as a professional management field. Some foreign experts and scholars in the field of data assets have established a professional forum on data asset management and organized DAMA International. Summarized DAMA DMBOK, a theoretical guidance system for data asset management.

Data asset management is a joint responsibility between data management professionals and business data management specialists in IT organizations. They represent the collective interests of data producers and data consumers.

The business data management commissioner acts as the data authorization principal, usually by experts and business leaders recognized in the relevant field, representing the data interests of his organization and taking responsibility for data quality and use;

Data management professionals are expert guardians and technical custodians of data assets, ensuring that data resources meet business needs by ensuring the quality of data and its metadata.

Data asset management generally considers ten major data management functions:

Data governance

Data architecture management

Data development

Data operation management

Data security management

Reference data and master data management

Data warehouse and business intelligence management

Document and content management

· Metadata management

Data quality management

Data asset management usually includes database administrator (database administrator)-database design, implementation and product support, and data management functions.

Data management is other management functions for data besides database management.