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Improving the chances of a successful MDM bake

by Saul Judah  |  September 26, 2014  |  Submit a Comment

So why didn’t my rye bread rise? – she asked. I’d been teaching a friend of mine how to bake bread over the past couple of months and ignoring the accusatory tone that suggested somehow I had sabotaged her attempt, we started the analysis.
The basic recipe I use is pretty simple – 0.5kg of strong white flour, 350 ml tepid water, 16 g of fresh yeast (7g of the dried stuff otherwise) and 10g of salt. Various methods will get you to the initial dough and I’m not really too precious about which technique is best – whatever works and feels natural is fine. The important bit is how it feels in your hands – the structure, which is just a matter of practice.
Trouble is, applying the same basic concepts might well get you very different results on different days. It might be too hot (the resting/proving may be faster), it might be too cold (resting/proving will be slower), it might be a bit stormy outside (humidity will impact the process) , your flour might not be strong enough, your oven might be too hot/cold, your water might be too hard/soft. And making bread is pretty easy compared with say, your MDM program 😉
Even if you use a well proven (no pun intended) MDM approach or technology like a cookie-cutter (there I go again), you will not get exactly the same results seen (or claimed) elsewhere. Of-course apply best practice, use an effective framework (The Seven Building Blocks of MDM), carry out due diligence on technology selection and so on. However you must find the time to stop and think – What’s different in the organizational environment that I am operating in? What business and market drivers are impacting my organization that are different from elsewhere? Based on the data domain (and attributes) I am mastering, what is different and what complexities are unique? Specifically what am I aiming to achieve and what exactly does a successful result look like? How must I implement MDM so that meets the requirements in manner that is economical and architecturally sound? The paper Five Vectors of Complexity that Define Your MDM Strategy therefore is a great way to think about the environmental factors within which your MDM program. Consider how the five vectors impact your MDM program context and importantly, do something about it.
Oh – and the ‘bread issue’ was traced to using all-purpose flour instead of strong flour. Yes – the packaged solution was not fit-for-purpose.

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Tags: data-quality  information-management  mdm  

Saul Judah
Research Director
1 years at Gartner
26 years IT Industry

Saul Judah is a Research Director on the Information Management team, focusing on master data management (MDM), data quality, and information governance and information risk. He works with Gartner clients on creating and delivering data quality strategy, establishing and running effective information governance programs, organizing and managing MDM programs and creating information risk control environments. Read Full Bio




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