by Angela Guess
Forbes contributor Dan Woods recently wrote, “The whole world has fallen in love with the value that data can bring. The work that must be done to unlock that value is far less popular… In the case of data, the fun stuff is playing with technology, distilling massive data sets using cool stuff like Hadoop, blending it together with systems like RedPoint or Alteryx, knitting it all together in Teradata, and then perhaps making a nifty chart or data discovery environment with technologies like Looker, Tableau or Qlik. Well, actually there is a lot of work in there, but it is an exciting to master a tool or discover something new.”
Woods continues, “The problem is that all across the world, such activities take place without first doing the work to determine the definition of the data going into the process. Where did this data come from? Is it the right data? Are we allowed to use this data? What other choices could we have made? How was it transformed? Are there any quality problems? And most important: Do we all understand this data in the same way? All of these questions fall under the rubric of the snooze-inducing term data governance. If there was ever something that shows up dressed in overalls and looking like work, it is the activities needed to execute a program of data governance.”
Woods goes on, “But let’s say that we answer all the questions listed above: How much more powerful does data become? How does it change the relationship between people and data in a business? …In my view, using ungoverned data isn’t the worst case—using no data is worse. But data that doesn’t have a clear definition as shown in Figure 1 leads to two situations, neither of which is good.”
photo credit: Flickr/ Sebastiaan ter Burg