Orion’s Enterprise Information Intelligence Graph (EIIG) provides proactive data quality management in the following ways:
- Finding the most optimal places (“hot spots”) in the overall data architecture to address data quality with least effort and most impact.
- Metadata Discovery provides insights of data assets that are critical for business usage.
- Data quality profiling will reveal if the data is fit for the usage.
- Data quality findings overlaid on data lineage point to where continuous DQ controls, rules & monitoring should be applied.
- Activating data stewardship – fact-based visibility enables them to justify and drive improvements to management of data assets and data quality
Recent Posts
- Understanding Active Metadata: Enhancing Data Management and Decision-Making Introduction
- EIIG’s Self-Defined Data Fabric and the Alignment with COBIT 5’s Five Principles
- How to Ensure Accurate and Trustworthy Reporting from Mainframe Data with Self-defined Data Fabric
- What is Metadata? A Brief Introduction to Metadata and Metadata Management
- Understanding Data Catalogs: The Key to Efficient Data Management