DATAForge drivel

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This blog was originally posted under: IM Blog

I have just read one of the most fatuous articles that it has been my displeasure to read over the last quarter of a century. Someone at DATAForge has posted an article on its website – and in a LinkedIn group, which is where I found it – called “Why data migration is not master data management“, which is pretty odd to start with, because it had never occurred to me that they were anything like each other. To be fair, that probably makes it a good title, in the sense that it makes you wonder what on earth the author is talking about and therefore check out the article.

Unfortunately, the gibberish doesn’t stop with the title. An early statement is that “when organizations feel their data is not being fully utilized, a common response is to upgrade to a new enterprise resource planning (ERP) system.” Really? I accept that some people are idiots and might upgrade for the reasons given, but this is “common”? I don’t think so. Far more likely is that they under lots of pressure from SAP (for example) to migrate to S/4 HANA: a subject I’ve discussed in detail elsewhere.

Worse is to follow. The author goes on to state that “the goal of an ERP system is to improve business intelligence (BI)“. I don’t know how to respond to this. It’s so far away from reality that my mind is boggled. But just to be clear, the goal of an ERP system is to automate business operational processes. A subsidiary benefit may be that you can generate information that can be used to derive actionable insight. Who cares about better BI? You care about better and more trustworthy insights.

I’m afraid that the folly doesn’t end there. The article goes on to say that data migration “is a single step … designed to move data from one location to another”. Funnily enough, this should properly be called “data movement”, as readers of my various research papers on data migration will know. Moreover, they will also know that one of the keys to successful data migration is to deploy data profiling and data cleansing tools. But the author writes as if this was not possible, going on to imply that using master data management is the only way to get good quality data. He specifically states that “Master data management (MDM), however, cleanses the data.” Which it doesn’t. Funnily enough you cleanse data by using data cleansing software. That might or might not be done in conjunction with MDM, but MDM itself does not do so and is not necessary for that purpose.

The sad thing is that there is a genuine case to be made for implementing MDM, but this drivel does not make it.

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