A cold contemplation of data quality


I have previously blogged about sneezing to unleash the data quality ideavirus, but in this post I have a different kind of sneezing in mind and, unfortunately, in nose. The common cold is so-called because it’s the most common human infectious disease. Despite the apparent irony of my traditional spring and summer colds, cold weather is not a cause. The common cold is caused by an upper respiratory viral infection. The rhinovirus is the most common cause, perhaps (albeit illogically) explaining my lack of fondness for rhinoceroses.

Poor quality could be called the common cold of data because it’s the most common data infectious disease. If left untreated, this infectious agent will negatively impact the quality of business decisions.

This cold contemplation is inspired by the fact I currently feel as if I have been trampled by a crash (i.e., a herd) of rhinoceroses. Actually I am simply suffering from the crushing effects of the rhinovirus stampeding through my upper respiratory tract while I lay on my couch contemplating such universal questions as:

  • Why does liquid cold medicine have to taste so absolutely awful?
  • Why is chicken soup the only type of soup that makes me feel better?
  • What evil genius invented a child-safety cap that sick adults couldn’t open?

Whenever I have a cold, I feel miserable and I can’t stop thinking about how I feel miserable – which, of course, only makes me feel even more miserable. When, just for fun, my symptoms magically disappear for about fifteen minutes, I feel so totally invigorated that I completely forget what it’s like to have a cold. Of course, when my cold returns from its fifteen-minute break, the crash of angry rhinoceroses return to crush me back into the deep recesses of the couch cushions while my thoughts slowly drift to how this could all be an analogy for how data quality is perceived by many organizations.

When everything is going well, nobody is concerned about possible data quality issues. Then all of a sudden, completely without warning, and apparently out of nowhere, the organization has caught the common cold of data. The business starts cleaning their keyboards and monitors with Lysol disinfectant spray, and washing their hands with anti-viral soap before and after touching any reports. IT puts all databases and file systems on a Vitamin DQ intravenous drip, and then applies Vicks VapoRub to all Ethernet ports while reading Chicken Soup for the Server. Executive management runs up and down the hallways screaming about being chased by a crash of giant invisible rhinoceroses with Kleenex tissue boxes for horns.

(Please note that in my feverishly disillusioned state, I may not have described all of those details accurately.)

My point (I think I had one) is that just like how I don’t think about preventing a cold before I catch one, many organizations only care about data quality when they are in the midst of a crisis caused by poor data quality. Once the immediate crisis is overcome (usually with a data cleansing project), the organization goes back to business as usual, forgetting all about poor data quality until the giant invisible rhinoceros inevitably rears its Kleenex tissue box horn yet again.

It’s time for me to take more liquid cold medicine (yucky) and chicken soup (yummy).


About Author

Jim Harris

Blogger-in-Chief at Obsessive-Compulsive Data Quality (OCDQ)

Jim Harris is a recognized data quality thought leader with 25 years of enterprise data management industry experience. Jim is an independent consultant, speaker, and freelance writer. Jim is the Blogger-in-Chief at Obsessive-Compulsive Data Quality, an independent blog offering a vendor-neutral perspective on data quality and its related disciplines, including data governance, master data management, and business intelligence.

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