The Big Picture of Metadata Management (MM) for Data Governance (DG) is indeed evolving to support today’s agile Enterprise Architectures (EA) where Big Data technology gets involved, new generations of Data Integration (DI) and self-service Business Intelligence (BI) tools play a bigger role, and where business users demand more metadata describing the deluge of new data, and better integration with their BI tools. To that end, a new generation of MM and DG applications are needed:

1. Web Data Modeling: Bridging the gap between the Business Glossary terms and the actual Enterprise Architecture data with business user friendly, web enabled, graphical data modeling apps:

• Data Store Documenter for physical data models of files, databases or big data (e.g. documenting Hadoop hive lack of relationships) offering automatic live database updates, live business glossary integration with semantic links (reuse or create terms on the fly), reverse engineering of naming standards, integration with data modeling tools (e.g. import/export ERwin)
• Enterprise Data Modeler for logical data models (e.g. data standardization and compliance)

2. Active Data Governance: Forward engineering to actual DI and BI tools:

• Forward engineer of well documented data stores into BI design tools (e.g. BusinessObjects, Cognos, Tableau) with user friendly names, description tooltips, and relationships as ready to use joins
• Business user friendly Data Mapping Apps with automatic forward engineering to actual DI design tools (e.g. Informatica, Talend)

3. Managed Business Intelligence: Live integration with BI Applications enabling BI users to use their MM application as a powerful multi-vendor BI Web Portal and BI Report Documenter allowing them to get live definitions from any objects on reports, add them in place if missing, trace data lineage from any object in reports, find other related reports (even in other BI tools), produce live report specific glossaries (e.g. Tableau worksheet)