by Angela Guess
David Loshin recently reflected on common issues surrounding master data models. He states: “As both the tools and the practices around MDM mature, we have seen some disillusionment in attempts to deploy an MDM solution, with our customers noting that they continue to hit bumps in the road in the technical implementation associated with both master data consolidation and then with publication of shared master data. Almost every issue we see can be characterized into one of three buckets.”
The three buckets are: “(1) Reference data issues, associated with misalignment of commonly-used master data sets, conceptual data sets, values domains, and various mappings across those ideas… (2) Structure issues, which often relate to differences in the source data models for similar data entity concepts (at the data element, table, and entity relationship levels) as well as differences between the source models, the master data models, and the downstream applications. (3) Semantic issues, in which isolated “meaning” differences that are specific to an application cause problems in aligning data entity relationships into a common model.”
