This week, my team is busy crafting
down a set of models that represent the future state architecture of the HR
line of business initiative. This group assignment may seem very challenging at
first, but it has turned out to be an interesting activity, from which I have
learnt a lot. One of the valuable lessons I have learnt from this assignment is
how to approach data stewardship.
Business
need to understand that quality of data is a business matter not an IT one.
Business processes work on data, therefore enterprises should ensure that data quality
is maintained by appointing the right subject matter expert Data Steward.
To
build an architecture that delivers real business value, data stewardship rules
that govern the valuation, creation, storage, use, archiving and deletion of data
should be defined. Key requirements of data stewardship should be developed and
mapped to the architecture Principles. This mapping reflects the integrity and consistency
of the architecture. Without these governance and mapping, we will end up with
an architecture that is not reliable to create business value.
I do
recall a discussion with an enterprise architect about data stewardship. His
company did not invest enough time and resources on data stewardship practices.
Their enterprise architecture failed to achieve business related metrics. Their
EA team had to fight a lot to sell the idea that business people should be in
charge of data quality.
At the end, it is important to note out
that data definitions should be defined in the context of the business and data
governance processes should parallel processes in other business units and also
it has to stay aligned with business objectives and activities.
See you next week!
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