The Standard

If “Good data makes lives better”

Then what is good data?

Your mind might jump to data quality and removing duplicates or filling missing values. But that’s a small part of what “Good data” really is.

In my home, we have a chart hanging on the wall marking the heights of my kids at different ages. At 3 years old one child was 35 inches, another child was 40 inches at 5 years old, and at 7 years old my eldest was nearly 49 inches. On and on it goes.

It’s enjoyable and nostalgic to revisit their heights at different ages, and maybe compare the growth curves at different points in time. But how tall they are doesn’t really matter much. Until you have a standard to measure against.

We planned a trip to a water park recently and beforehand we read online about the height requirements for some of the rides. Quickly I shuffled each of my kids against the wall chart to see how they “measured up” to a standard. The oldest two cleared most of the requirements. The youngest will need to wait a couple of years before he can ride everything.

Once we knew what was required, we had something to compare against. Sure, it was an arbitrary standard that doesn’t hold any meaning for the rest of life. But in the world of the waterpark, the height requirement was the law. It was a binding standard by which everything else had to be measured.

Good data meets the standard. It measures up.

The expectations, requirements, and usefulness of data will vary based on the work I do and the data I need. But there is always a standard.

Sometimes an unexpressed standard. Ideally, clear and thoughtful standards.

Over the coming days, I’ll share what I think “good data” standards are. And specifically what the standards are that make lives better.

I’m here,

Sawyer