The Master Data Management (MDM) discipline is emerging. A certain trend is that MDM solutions will grow beyond handling traditional master data entities and encompass other kinds of data and more capabilities that can be used for other kinds of data as well.
This include:
- Utilizing data discovery to explore data sources with master data, reference data, critical application data and other kinds of data as described in the post How Data Discovery Makes a Data Hub More Valuable.
- Governing the full set of data that needs to be governed as examined in the post Maturing RDM, MDM and ADM With Collaborative Data Governance.
- Building a data hub that encompass the right representation of data that needs to be shared enterprise wide and even business ecosystem wide as explained in the post Why Flexible Data Models are Crucial in Data Sharing.
- Measuring data quality in conjunction with general key performance indicators in dashboards that besides master data also embraces other internal and external sources as for example aggregated data from data warehouses and data lakes.
These themes were also covered in a webinar I presented with Semarchy last month. Watch the webinar The Intelligent Data Hub: MDM and Beyond.
Liliendahl on Data Quality 