Data Governance and Data Profiling

In our customer base, we find that a number of clients have implemented a Data Governance program based on a consultant’s “People and Process” approach that to all intents and purposes ignores the role of Data Quality tools, particularly Data Profiling and Data Quality dashboard solutions, for the Data Governance program.

Data Stewards meet periodically to log data quality issues, such as “The credit card data is bad”, in the Issue Register. spreadsheet.  Without meaningful metrics the impact of these issues cannot be accurately assessed, nor can sensiblel corrective action be taken. The Data Governance program runs the risk of becoming bloated and beaurocratic, without being able to demonstrate business value and, in the worse case, may fail to gain business support.

Data Profiling and Data Quality score carding tools allow the governance team to quickly and easily generate meaningful metrics, “such as 17% of credit card numbers are have invalid expiry dates captured – our goal is to bring this to  less than 5%.”  Specific corrective action can be suggested and, over time, improvements to underlying data quality can be measured and communicated to business – proving the value of the program.

While some metrics can be generated using traditional queries or analytical tools this process requires technical competence and does not easily lend itself to business friendly metrics such as “number of invalid credit card numbers.” Bloor Research also makes the point that this kind of repetitive analysis is boring and tends to be allocated to junior staff, who may not have the business acumen to define the most relevant measures.

If the objective of Data Governance is to improve the value of the organisation’s data then Data Profiling tools and Data Quality scorecards are critical to success.

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