If a principle goal of data governance is to create context for the use of data within a company, which it is (as discussed in the post Why do you need data governance?) then data governance must include the definitions of terms – so called metadata management.
Is there a difference between technical metadata (data flows, data models, data quality attributes, etc) and business metadata – such as data policies, business glossaries, and the like?
Is all metadata equally valuable?
Does all metadata need to be governed?
When two people are talking about metadata are they likely to be talking about the same thing?
The irony for me, is that metadata is by definition ambiguous – data about data – as discussed in the post What is metadata anyway?
The next time you are discussing metadata make sure that the entire room is working with the same definition. Otherwise you may just be adding to the confusion.[Tweet this]
Once we have defined the technical context we still need a business context.
A key finding of the 2014 Forrester Wave for Data Governance is that data governance has shifted from a technology management endeavor to a business imperative.
You can download the report from the link provided, or read more about it here – Data governance 2.0: Who has what it takes?
Take the data governance poll [Tweet this]
Redefine the way you look at data governance!
Data assets that cannot be easily used by business data stewards may as well not exist. Data governance must create the link between the business goals and policies, to the technical metadata that defines the environment. This requires a new tool – the data stewardship platform – that create the link between the business and technical layers.
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