Data Governance (Part One)

This is the first of two articles introducing the concept of data governance.

Consultants and experts in the BI field use the terms “data governance” and “data integration” to talk about how to approach the kinds of problems we’ve been discussing in this section of the material. These fundamental concepts lie at the heart of the “integrated and coordinated” part of the definition we gave earlier for BI as a whole.

When we defined BI we said that both the data and the definitions of what the data mean need to be shared. “Data Governance” is the term that BI professionals use for the process of making sure that happens. This includes things like setting policies and procedures for how data are to be captured, processed, and stored, defining what terms like “revenue” mean for the purpose of making business decisions, defining what is acceptable for knowledge workers to do with data that are being used for decision purposes, and more. In short, what is being governed is the BI life cycle itself.

How data governance works depends mainly on the number of people with a stake in the process. In a small business, the owner may be the only person with a stake. So that owner will call the shots. In a larger business there may be many people of relatively equal clout with a stake in the governance process, and a significant amount of time and effort may need to be expended to make sure each voice is heard. In many larger companies today you may actually find a data governance board, made up of representatives of the IT and non-IT business units, whose mission it is to set corporate standards, policies and procedures for data governance.

Next time: The importance of top management buy-in for successful data governance.