One of the jobs computers superseded was that of... the computer. A “computer” was somebody who worked out things like tide tables or mortality rates using slide rules and hand-cranked tabulators and good old mental arithmetic. (What we call a computer was originally given much sexier names – like “electronic brain”.)
As data standards become more and more accepted as the gateway to understanding – and exploiting – data, there's another role at risk of redundancy. This is the labor of wrangling disparate data so it can be analyzed as a single collection. The work is usually buried under a more positive sounding role designation. Many well qualified and highly motivated data scientists are frustrated that they spend so much of their time dealing with disparate data instead of developing insights and actionable intelligence.
We can achieve a lot for business and society by implementing effective data standards. We know data standards save money, speed up processes, and enlarge networks. But we should remember data standards also liberate people from pointless drudgery. No one trains for a profession in hopes they'll spend most of their work life sweeping the floor or rearranging the shelves. Let's remember data standards are the major enabler for real digital business.
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