Data Quality Mischief Managed

Even if you are not a fan of Harry Potter (i.e., you’re a Muggle who hasn’t either read the books or at least seen the movies), you’re probably aware the film franchise concludes this summer.

As I have discussed in my blog post Data Quality Magic, data quality tools are not magic in and of themselves, but like the wands in the wizarding world of Harry Potter, they channel the personal magic force of the wizards or witches who wield them.  In other words, the magic in the wizarding world of data quality comes from the people working on data quality initiatives.

Extending the analogy, data quality methodology is like the books of spells and potions in Harry Potter, which are also not magic in and of themselves, but again require people through which to channel their magical potential.  And the importance of having people who are united by trust, cooperation, and collaboration is the data quality version of the Order of the Phoenix, with the Data Geeks battling against the Data Eaters (i.e., the dark wizards, witches, spells, and potions that are perpetuating the plague of poor data quality throughout the organization).

And although data quality doesn’t have a Marauder’s Map (nor does it usually require you to recite the oath: “I solemnly swear that I am up to no good”), sometimes the journey toward getting your organization’s data quality mischief managed feels like you’re on a magical quest.


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