David Loshin, president of Knowledge Integrity, Inc., is a recognized thought leader and expert consultant in the areas of data quality, master data management and business intelligence. David is a prolific author regarding data management best practices, via the expert channel at b-eye-network.com and numerous books, white papers, and web seminars on a variety of data management best practices. His book, Business Intelligence: The Savvy Manager’s Guide (June 2003) has been hailed as a resource allowing readers to “gain an understanding of business intelligence, business management disciplines, data warehousing and how all of the pieces work together.” His book, Master Data Management, has been endorsed by data management industry leaders, and his valuable MDM insights can be reviewed at mdmbook.com . David is also the author of The Practitioner’s Guide to Data Quality Improvement. He can be reached at loshin@knowledge-integrity.com.
We have looked at two reference data sets whose code values are distinct yet equivalently map to the same conceptual domain. We have also looked at two reference data sets whose values sets largely overlap, though not equivalently. Lastly, we began the discussion about the guidelines for determining when reference
In my last post I discussed isomorphisms among reference data sets, where we looked at some ideas for determining that two reference data sets completely matched. In that situation, there was agreement about the meaning of every value in each of the data sets and that there was a one-to-one
In my last post we started talking about the tasks associated with data harmonization; the topic of this week’s post is determining that two reference data sets refer to the same conceptual domain. First, let’s review some definitions: A value item is a representation of a specific value meaning in
A few weeks back I noted that one of the objectives on an inventory process for reference data was data harmonization, which meant determining when two reference sets refer to the same conceptual domain and harmonizing the contents into a conformed standard domain. Conceptually it sounds relatively straightforward, but as
In one of my prior posts, I briefly mentioned harmonization of reference data sets, which basically consisted of determining when two reference sets referred to the same conceptual domain and transforming the blending of the two data sets into a single conformed standard domain. In some cases this may be
There are really two questions about reference data lineage: what are the authoritative sources for reference data and what applications use enterprise reference data? The criticality of the question of authority for reference data sets is driven by the need for consistency of the reference values. In the absence of
Last time we looked at some of the benefits to be derived form managing the metadata associated with reference data. Practically speaking, the first step in managing the metadata for reference data is to identify which reference data domains exist and document how those domains are used. That suggests taking
In my last set of posts I started to look at some of the challenges associated with enterprise management of reference data domains, especially as the scope of use for the same conceptual reference domains expands across databases, systems, and functional areas within the organizations. Recognizing the value of capturing
The first step is establishing governance for reference data is assessing the existing reference data landscape: understanding what reference data sets are used, who is using them, and how they are being employed to support business processes. That suggests a three-pronged approach to identifying organizational business process and application dependencies
In my last post, I shared some thoughts about challenges associated with the lack of management for reference data, such as reinterpretation of semantics and the inconsistencies that crop up when multiple copies are used. All of the challenges I mentioned are indications of a need for improving the enterprisewide
