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August 22, 2018

There’s a big difference between good data and interesting data.

Good data is often very boring. It contains the basics and comes in as expected (right format, schedule, completeness). There are lots of things we can do with good data in order to move the ball forward.

Interesting data is never boring. It contains interesting attributes and never-before-seen elements. Usually it comes in as a one-off dataset. There are many interesting things that can be done with interesting data but sometimes it is hard to tell if those interesting things are valuable.

Recently, I’ve been involved with a few technology companies looking at their new capabilities in development. There are some truly fascinating things being developed. My first question every time is, does this new feature drive user adoption of the system? Stated another way, does this new feature give users a reason to either contribute data more freely/voluntarily or come back regularly? If no, then you are developing a second tier feature. If yes, it’s a core feature that is making your system better.

Most interesting data comes from second tier features. It’s the data that may or may not be correlated to the main data. It may or may not be indicative of performance. But my goodness can it show some interesting things…..those things just may not mean anything.

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