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Data Quality with no process is not the same as “lean MDM”

by Andrew White  |  February 19, 2016  |  1 Comment

I noted some muses that the “MDM team” at Gartner came up with as we discussed topics likely to be discussed at the upcoming Enterprise Information and MDM Summits in London, UK (March 2-3), and Texas, USA (March 16-18).  I plan to explore each one to explain our thinking.

The first and second muse are related and they were:

  1. Data Quality with no process is not the same as “lean MDM”
  2. Data Quality with process is also not the same as MDM

These muse encapsulates several points, and semantics are important:

  • Data Quality in this muse is equated to the collection and use of tools referred to as data quality.  Most of these tools, though not all, are targeted at IT users.  A recent trend in the DQ market is that some of the technology is being adapted and evolved toward business users.
  • MDM is really a process or discipline, not a technology.  Though there are solutions called MDM, the point is that MDM is a technology enabled, business led, discipline, program or method.
  • Lean MDM or agile MDM are hyped concepts, most often by vendors, that try to play on a silver bullet idea: that you can get the benefits of MDM without the assumed high costs of an MDM solution or changes necessary in a business and how it behaves.

There is no such thing as Lean MDM

To assure semantic consistency of master data (not all data) a business has to create data in a different way to most practices established over the last 20-30 years.  This is because we have spent our  money and time mostly on building silos.  Thus trying to assure semantic consistency across silos after the fact tends to incur a lot of change to how the business operates.  The answer is not to reduce or limit the change, and increase the costs of a technology to solve the problem.  Nor is there a cheap technology to solve the problem.

So we should be clear and call a spade a spade.  Lean MDM really means something like starting an MDM program but focusing on the narrower use of data quality tools to improve the data quality.  This lacks a lot of the work and changes needed to make operational (i.e. embed into day to day work of the business) the work of sustaining semantic consistency of master data.

Of course, if you decide to change the scope of the semantic definitions above, you might conclude that “data quality is a process” and not just a set of tools.  This is valid.  But if you take this approach you have to accept that “data quality as a process, focused on master data, with all the supporting operational governance and stewardship and integration and so on, is equal to MDM’.  And so we have come full circle.  Because data quality was not perceived as a process, MDM emerged.

Let’s argue the difference at our upcoming summits.  I will be handing out silver bullets.  See you there!

 

 

Category: data-quality  master-data-management  mdm  mdm-of-customer-data  mdm-of-product-data-mdm  silver-bullet  

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


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  1. […] I noted some muses that the “MDM team” at Gartner came up with as we discussed topics likely to be discussed at the upcoming Enterprise Information and MDM Summits in London, UK (March 2-3), and Texas, USA (March 16-18). I plan to explore each one to explain our thinking. The first and second muse are …  […]



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