Data Governance + Quality = MDM

road-to-damascusSt Paul’s epiphany on the road to Damascus was a defining moment in the history of the early Christian church.

This was the moment when Paul, the devout Pharisee and oppressor of Christianity was converted to become the early church’s biggest evangelist.

A recent planning session with a client, while not comparable in terms of global impact, delivered a similar insight and shift in perspective.

During a routine MDM planning session we broke our approach down into various streams, namely:

  1. Data Governance
  2. Data Quality
  3. Data Integration
  4. Master Data Management
  5. Data Architecture

We  then defined the high level outcomes for each stream – for example:

  • For data governance our high level objective is to Have the business take responsibility for data and put the processes in place to support this
  • For data quality our high level objective is to Provide data that is fit for purposes
  • For data architecture we ring fenced our view to focus on the architecture to support the client master – with various design objectives and goals.
  • For data integration our goal was defined as to Integrate and synchronise customer data from the source systems to the target MDM application

This was when the Eureka moment occurred for one of the senior IT managers present.

“If we get that right we have MDM,” he said. “We don’t need a separate stream!” [Tweet this]

That data governance and data quality are critical to successful MDM is well accepted.

Yet, in most cases these components get insufficient attention from IT who prefer to focus on the implementation of an MDM product.

This revelation was when IT shifted from the “implement a tool” mentality to the “create business change” mentality.

Our project has a long way to go and evolve. But this may well have been a defining moment in assuring its success.

 image sourced from




One thought on “Data Governance + Quality = MDM

  1. Interesting equation.

    Let us look at the other permutations.

    How about DG + MDM + CIM = DQ

    Where CIM=Common Information Model.

    The equations must be read as follows:

    Many efforts at improving data quality are project-based and fizzle out once the project is completed, only for the problem(s) to re-occur.

    Data governance is one of the many ways to sustain the quality of data beyond a project.

    But without tools, data governance might, at best, remain pieces of paper on the wall. That is where a MDM platform comes it its own. It brings data governance to life. Data stewards have a window through which they can monitor data and make it part of their everyday job. MDM, by default, is founded on and implements a Common Information Model around which Business and Technical Metadata can be hooked.

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