Data Quality 3.0 Revisited

Back in 2010 I played around with the term Data Quality 3.0. This concept is about how we increasingly use external data within data management opposite to the traditional use of internal data, which are data that has been typed into our databases by employees or has been internally collected in other ways.


The rise of big data has definitely fueled the thinking around using external data as reported in the post Adding 180 Degrees to MDM.

There are other internal and external aspects for example internal and external business rules as examined in the post Two Kinds of Business Rules within Data Governance. This post has been discussed in the Data Governance Know How group on LinkedIn.

In a comment Thomas Tong says:

“It’s really fun when the internal components of governance are running smooth, giving the opportunity to focus on external connections to your data governance program. Finding the right balance between internal and external influences is key, as external governance partners can reduce the load/complexity of your overall governance program. It also helps clarify the difference between a “external standard” vs “internal standard”, as well as what is “reference data” vs “master data”… and a little preview of your probable integration strategy with external.”

This resonates very much with my mindset. Since 2010 my own data quality journey has increasingly embraced Master Data Management (MDM) and Data Governance as told in the recent blog post called Data Governance, Data Quality and MDM.

So, in my quest to coin these 3 disciplines into one term I, besides the word information, also may put 3.0 into the naming: “Information Quality 3.0”, hmmm …..

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