BeyeNetwork Article

A template for a data quality environment in a meta data model

Jonathan Geiger, BeyeNETWORK Contributor

This article originally appeared on the BeyeNETWORK.

We presented Part 1 of the Meta Data Model in our last issue of the Bill Inmon

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Newsletter (See recently published articles below).  Part 2 of this model addresses the data quality environment subject area.  The Data Quality Environment subject area is the portion of the model that contains information about the quality expectations and the on-going information about the quality being processed.  This area will become increasingly important as companies apply meta data in support of Sarbanes-Oxley and other regulations. 

This subject area contains two sets of tables; one set with the data itself and the other set with the processes that handle the data.  The four entities in the subject area are: 

  • Data Quality Column Criteria – The Data Quality Column Criteria contains information about the data quality expectations for each column of interest.
  • Data Quality Column Measurement – The Data Quality Column Measurement contains the on-going metrics related to each of the data quality expectations.
  • Process Quality Criteria – The Process Quality Criteria contains information about the data quality expectations for each data migration process of interest.
  • Process Quality Measurement – The Process Measurement contains the on-going metrics related to each of the process expectations. 

One of the critical aspects of any data acquisition strategy is the inclusion of audit and control processes.  The Data Quality Environment subject area stores the information relating to this process.  Inclusion of the audit and control information does more than just enable companies to substantiate the accuracy of the processes – it enables them to do it quickly.  Being able to quickly substantiate the accuracy is extremely important in maintaining credibility. 

A copy of this portion of the meta data model is included with this article.  This is additional information for your starter model.  As you apply it to your environment, you may need to include additional entities and attributes.  Also, to ensure that people understand the content, be sure to provide the meta data for the meta data model in the form of definitions for each of the entities and attributes.  


In summary, take the best from our model and make it your own.  Use it to compare to the models presented by the vendors or to create your own robust meta data architecture. 

Look for future articles that will include the remaining subject areas to complete this model.  For more information or questions, contact either Jonathan or Joyce at the e-mail addresses shown below.

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