Properly Extracting Value from Data

Is big data overrated? In a world ruled where metrics are king, raw data is being used to assess the quality of subjective things. We use big data to quantify the quality of teachers, students, and our fitness, but what insights are we drawing from that data?

In the mid-nineties, websites like Facebook were using human judgement to help discern quality insights over mindless data. Asking people how they felt about what was presented to them in their newsfeed granted them insight on what was an absent-minded click and what was an actual engagement.

Big data often fails to consider human factors that are often left unaccounted for. In the case of teachers, big data may determine that a certain teacher is doing poorly, but small data will tell us why that is. Conversely, it can tell us what a teacher is doing right to yield better results amongst children. Big data does a great job of explaining results, but a poor job of explaining how or why you got there. There is no replacement for human inspection and expertise, as much as companies try to avoid doing so.

As optimistic as we’d like to be about using big data to improve our lives and save us money, we can’t let it replace traditional decision making. Instead, we should use it as a tool to make more educated decisions.

To read the full article on The New York Times, click here.