Organizations are faced with an increasingly complex data landscape, finding themselves unable to cope with exponentially increasing data volumes, compounded by additional regulatory requirements with increased fines for non-compliance.  Enterprise architecture and data governance are often discussed at length, but often with different stakeholder audiences.  This can result in complementary and sometimes conflicting initiatives rather than a focused, integrated approach. 

In my Dataversity webcast last week, I discussed the importance of enterprise architecture alignment with business strategy and goals.  Enterprise architecture must  be built upon a solid data architecture foundation.  Data architecture supports the entire structure, comprised of business architecture as the central pillar, as well as application and technical architectures.

 

This requires integrated modeling, spanning the different aspects of enterprise architecture ranging from high level context through detailed implementation.  For data architecture in particular, it is essential to understand the data value chain, as well as the full data life cycle.  This also requires comprehensive business process modeling to provide the necessary context of how data is utilized in your organization. 

The replay of the webcast is now available for viewing HERE.

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