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Good Data is the New Black
Clean, integrated data is no fad
Good, clean, standardized, reconciled, matched, integrated data is a business basic and until we embrace the formal mechanisms to clean it up, we’re simply mixing plaids with stripes.
Fashion is fickle, and today’s fabulous frock can quickly become tomorrow’s housecoat. I once owned a pair of gauchos (a short version of bell-bottoms, or a long version of culottes). Suffice it to say that on a good day I could look positively de rigueur. There was that Indian-themed poncho, circa 1975, complete with fringe. At the time I was mainstream chic, but there is no way I could wear it today in a public square.
Colors, patterns, and fabrics may come and go, but black, as they say, is always in style. Packing my carry-on for a recent trip to New York was super easy. Casually fling a pencil skirt, a few pair of tights, and a turtleneck, patent leather pumps, and some pearls -- all of them black -- into the garment bag (yes, also black), and you’re ready for a couple of days’ worth of client meetings, a play, and dinner at Balthazar!
(Truth be told it rained in torrents and I stuck to my hotel room where I had room service in my lime green Life is Good flannel PJs, but I like the image of flinging a totally black wardrobe into my luggage in an Audrey-Hepburn-meets-Betty-Hutton kind of way, so please don’t rain on my parade.)
This brings me to data quality. I think good data is the new black. After all, it makes everything so much more straightforward. With good data, marketing campaigns are more relevant. Risk scoring is more accurate. Reporting to the street or to the feds is more reliable. You can take good data to a service-oriented architecture and make the whole thing so much better. You can take it to a call center rep and boost your customer sat scores. You can take good data out like a debutante, and waltz it around your company and brag about what a promising future it has!
Not having good data is way more risky. We skip development steps, demur in investing in automation, and ignore data correction prior to application deployment. Everyone knows it’s a crap shoot, but people still try to pull it off. Bad data is the fashion version of wearing yellow: very few can really get away with it. For those who try and fail, the consequences can be disastrous.
Sartorial metaphors aside, it’s time to focus on good, clean, integrated data. It’s the year to invest in automation. It’s time to convince your management that enterprise data management is no longer an intellectual pursuit, it’s a bona fide need. It’s time we take data quality out of the project and into the enterprise. Good, clean, standardized, reconciled, matched, integrated data is a business basic and until we embrace the formal mechanisms to clean it up, we’re simply mixing plaids with stripes.