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As data professionals, we are living in the golden age of “DATA.” Data is king. Consulting firms and CEOs alike are proclaiming “data is the new oil” that will run our information economy for years to come.
The question I ask each of you then is this: “How will we turn this valuable asset into something concrete that the organization can leverage?”
In the past, appliances like Teradata or Netezza would proclaim you as a champion if you had the appliance. Today we hear that the cloud will allow us to manage our vast amounts of data. Tomorrow it will be quantum computing. Unfortunately, in my opinion, none of this will help unless you fully understand what it means to take a data-focused approach.
Taking a data-focused approach means understanding your data from a data perspective, not a business perspective. This sometimes causes my colleagues to look at me funny, because you always want to help the business. But if we want to get the true value out of our data, we need to start realizing that data professionals have a unique perspective. The following (not exhaustive) list provides a few examples of what you need to do to drive value from your data. You need to understand:
- Data flows within your data echo sphere
- Data definitions within your data echo sphere
- Data privacy regulations
- Data security within your applications and company
- Data lineage within your data echo sphere
- Data Quality within your data echo sphere
- Data owner/stewards need to have the right skills
Let me provide an example from my past. We were asked to pull data from an application system for the business because they wanted to do some analytics on the data. No biggie – that happens every day now. The business said we don’t need to understand the application logic or review the metadata that was created. “Just get us the data,” they said. We argued that effort was needed to understand the data, but we were directed by senior management to “just pull the data.” The results were not what was expected. The business said we did it incorrectly because “it’s not the same as the screens in the application system.”
When we went back to the application team, they told us the logic in the application changes the data on the screen but not in the underlying tables. If we had metadata or data flows providing us insight into how the data moves in the application, we could have saved one month of effort in getting out of the mainframe.
There is a big difference between “data-focused” and “data-driven.” There is also a balance. The faster you leverage your data, the more efficient you are or the more top-line revenue you bring in. But there are times when being data-focused can help you cross the finish line faster.
Until we understand the difference, we will not be able to leverage our data to its maximum – which is truly disappointing to data professionals. And, more importantly, it will be truly disappointing to shareholders who will never realize the ROI for an asset within the companies they own.