Data Asset Management Capabilities General Requirements do not include the establishment of an organization-level data asset management platform.

I. Data Asset Management Definition

It is a set of business functions that plan, control, and deliver data and information assets, including the development, implementation, and oversight of plans, policies, programs, projects, processes, methodologies, and procedures related to the data, in order to control, protect, deliver, and enhance the data assets' value.

The data asset platform is located in the middle of the bottom layer and the application layer, and is in the position of carrying on the top and bottom, supporting the development of data applications oriented to value creation on the top, and realizing the management of the whole life cycle of data on the bottom relying on the big data development platform.

Data asset management runs through the whole process of data collection, storage, application, and destruction of the whole life cycle, and data asset management is the management of its assets.

Data asset management needs to have the ability to

1. Comprehensive grasp of the current status of data assets

The need for a comprehensive inventory of data assets, the formation of data maps, unified view, metadata management, can be different dimensions to speak of the data asset The data can be displayed in different dimensions to help the business to quickly locate and understand the data, and to effectively monitor the data.

2. Improve data quality

According to the data quality monitoring mechanism, data assets are monitored in real time to grasp the data quality situation; through the formulation of data lifecycle specifications, to strengthen the whole process of controlling the data governance, and to realize the transformation of the data into high-quality assets.

3. Realize data interconnection

By formulating unified data standards, establishing a data **** enjoyment system, and improving the process specifications related to data application, authority management, data collection, transmission, and use, it breaks down the data silos, and provides a platform for the development of data circulation.

4. Enhance the efficiency of data acquisition

Data analysts need to spend 80% of their energy on data preparation, and by building a data asset management platform, data can be acquired quickly.

5. Ensure data security compliance

Data security is the bottom line of data asset management, through the development of a comprehensive data security strategy, from the permissions, classification and grading, security audits and other all-round security control, to ensure that the data acquisition and use of legal compliance.

6. Continuous release of data value

Management, establish a set of data-driven organizational management system processes and value assessment system. On the technical side, the construction of a modern data platform and the introduction of intelligent technology ensure that the data asset management system platform continues to serve the data asset management system in a healthy manner.