1.Research achievements of the project
Establish a data governance platform to achieve the following: automatic metadata collection, automatic data lineage acquisition, data impact analysis and lineage analysis, data model and version management, data asset catalog management and display, external data asset catalog maintenance, publishing, and shared query, data standard management, daily evaluation and trend analysis of information system standard implementation/compliance, data quality analysis, data quality assessment, closed-loop management process for data quality issues, evaluation and quantitative assessment of data quality and data governance work, maintenance and management of data governance strategies and rules, and maintenance and management of data governance activities and plans;
Implement the outcomes of data governance consulting to achieve online process-oriented and automated management of data standards, data quality, and metadata; establish a data asset directory and data map, and develop a comprehensive data governance statistical analysis dashboard.
2.Customer needs
- Metadata acquisition, retrieval, management, and association
- Data lineage acquisition and analysis
- Data standard management, bid submission
- Data quality analysis, data profiling
- External data asset directory management
- Data quality management assessment process
- Data standard implementation/compliance management assessment process
- Data asset map
- Visual analysis of data governance work
- Comprehensive portal for data governance
3. Functional structure diagram of the system
3.1 Functional architecture diagram of enterprise information management service process
4. Advantages of IBM’s solution
Promote the business department’s management of data ownership
End-to-end data association and inheritance
Support adaptive deployment across multiple clouds, including public clouds, private clouds, and on-premises environments
Provide keyword-based graphical search to quickly obtain relevant information and data graphs
Easy to use, rich information access
Provide social communication functions, such as liking and commenting, to enhance platform usage stickiness
Provide data quality scoring and present data quality trends
Multi-dimensional evaluation data
Automated data quality rule evaluation
Accelerate data governance through automation and machine learning
