Data cleansing is an important part of any migration exercise. It’s like letting go of the old and useless, and adapting to the new and useful. Migrating from an old technology to a new technology, from an old business model to a new business model always requires data cleansing to be performed on the source data.
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Dirty minds, if you ask me. Or may be naive big-shots who don't have knowledge of programming terms. Because according to Wikipedia, “Quick-and-dirty is a term used in reference to anything that is an easy way to implement a kludge. Its usage is popular among programmers, who use it to describe a crude solution or programming implementation that is imperfect, inelegant, or otherwise inadequate, but which solves or masks the problem at hand, and is generally faster and easier to put in place than a proper solution.”
Well, the poor person who made the slide had other intentions, in line with the wikipedia definitions. Intentions were to “quickly” set up the data even if that meant data was “not so clean” or “dirty”. Well, obviously he was misunderstood by the elite cabal. Idea was simple – given the data has no use for future processing, is static and drives no revenues or reports and needs to be set up one-off just for the reference in the database, there is no point spending time and money on cleaning the data to give it a correct & meaningful shape. After intermittent bursts of laughters and grins among all big waves, the plan is (still under review) to keep it quick and dirty, until ofcourse the management cabal comes up with some "calm and clean" ideas!
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