Category Archives: Data Quality

Data Quality Manifesto

In the software industry, the Agile Manifesto has become the “silver bullet” in recent years.  While I have seen many software practices that appeared more “fragile” than “agile”, the Agile Manifesto itself is an amazing concept that should be read by all software developers.

It occurred to me some years ago that there were some “self evident truths” that applied to data quality, and so I proceeded to put together the Data Quality Manifesto below.  It has evolved a little over the years, but I believe that it still has value as a starting point in the consideration of all things related to data quality.

The Data Quality Manifesto:

As a data professional, I hold the following truths to be self-evident:

  1. After its people, an organisation’s most valuable asset is the data it collects, manages and uses to support its operations.
  2. Poor quality data is more dangerous than no data: decisions made without data are known to be risky, but decisions made on poor quality data are incorrectly assumed to be sound.
  3. Like the physical assets of an organisation, the data assets of the organisation will degrade without regular scheduled maintenance.
  4. Real improvements in data quality come from pro-active monitoring of the strategic data elements, not reactive correction of tactical errors.
  5. Changes to data should be subject to all the same rigour of requirements gathering, design, documentation and testing that any other coding process would undergo.
  6. Full understanding of the data assets can only come from an understanding of how that data interacts with the business processes, applications and users.
  7. Data quality is not the result of commitment, processes or technology, but rather a fusion of these three things.