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More on Governance of Master Data

by Andrew White  |  October 2, 2009  |  2 Comments

I blogged yesterday about two of the main use-cases of MDM: operational MDM and analytical MDM.  Mark Beyer and I would “argue” if there was a way to denote the primary difference of the two, with respect to governance.  I explained that in operational MDM, governance is “active” and in analytical MDM, governance is “passive”.  I felt this was a good way to describe that in the former, there is explicit, business involvement day-to-day, to take decisions that changed processes and data in order to achieve and sustain, “single view”.  In BI land, with analytical MDM, the work is much less day-to-day, in that rules are created by IT to be invoked during a data load.

In analytical MDM there is no message or alert sent to a business user, that is resolved during the normal cycle of work events.  It would be more of a project, rather than a process.  This is a major difference between the two domains; and a difference that must be taken heed of.  Too many users miss the point and assume that what works with BI will work with MDM.  I hear, too often, the comment, “I can ‘do’ MDM with my BI/data warehouse”.  This is partially true in terms of the mechanics; but in terms of the process.

Mark is very fair, and logical, and he says that there is no governance in BI.  He is very right, since for him, governance implies activity (not just mechanical rules).  So we do agree; we just differ how we name the condition.

Guided Governance versus Mechanical Governance

Given that analytical MDM and operational MDM share common mechanics, it is easy for BI technology to be used (i.e . demonstrated) to support governance.  The problem is that this is not the entire solution.  I saw a vendor demonstrate a new “governance application” that showed, reasonably nicely, numerous mechanical activities a user would follow day-to-day.  These mechanics supports an operational MDM environment – they could be seen to support day-to-day, business user activities that they would have executed anyway.

What was missing from the briefing was, as I said on the briefing, “guided governance”.  The vendor had no demonstrable technology that provided the business user with analytics and metrics related to data quality, process exaction, or process design.  As such, there were no guard rails or searchlights highlighting where business users (i.e. stewards) need to work their magic.  It is like piloting an aircraft with a manual; everything goes great until environmental conditions change for which the manual cannot predict and instrumentation is needed to guide the user to make a decision.  As with the example, bad news is what happens as a result of this lack of instrumentation.

I called this instrumented environment, “guided governance” versus the more common “mechanical governance” that this, and most other vendors, is initially focused on.  It won’t be long before users help the vendors out and tell them what they need (once they start flying those planes).

Category: analytical-mdm  governance  operational-mdm  

Tags: analytical-mdm  governance  operational-mdm  

Andrew White
Research VP
8 years at Gartner
22 years IT industry

Andrew White is a Distinguished Analyst and VP. His roles include Chief of Research and Content Lead for Data and Analytics. His main research focus is data and analytics strategy, platforms, and governance. Read Full Bio


Thoughts on More on Governance of Master Data


  1. Winston Chen says:

    Yes, the support for business ownership and their active participation in maintaining master data is the key criteria for whether a vendor’s solution is “governance enabled.”

    Following this logic, would you conclude that quite a few of the operational MDM vendors are very weak in governance? Or, in the terms outlined here, they’re doing passive governance, rather than active governance? They’re more about transactionally processing incoming data in the backoffice and distributing masters based on IT-defined rules?

    Great point about “guided governance”. Too many data management products are not designed with process in mind. Got to look at the day-in-the-life of the end user.

  2. Virginia says:

    Regarding;
    I explained that in operational MDM, governance is “active” and in analytical MDM, governance is “passive”. I felt this was a good way to describe that in the former, there is explicit, business involvement day-to-day, to take decisions that changed processes and data in order to achieve and sustain, “single view”. In BI land, with analytical MDM, the work is much less day-to-day, in that rules are created by IT to be invoked during a data load.

    I think I have news for you:
    You are right in defining the MDG (MD governance) in this way. Because this is the real life,
    however
    The MDG must not be passive regarding the analytical MDM but
    PROACTIVE!
    however this is the dream,
    because MDG people are usually not mathematicians…and herby not analytical enough to manage the evaluation of the MDM business processes.
    Your opinion?
    thanks
    Virginia



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