June 21, 2013 - by rachelbalik
In any scientific discipline, asking questions is the key to progress. You have a hypothesis, you create an experiment, you test it, and if it’s wrong, you still learned something. As we all know, exploration for exploration’s sake leads to some of the world’s greatest inventions. For example, the transistor is arguably the most important invention of the 21st century, but we couldn’t have built one without first discovering semiconductors. Science advances because it builds on itself. A process of trial and error ultimately results in big wins.
Arguably, the same rules apply to data science. We’re discovering more each day about how big data can have huge impact on business, but the reality is, we’ve only scratched the surface of what’s possible. We know what we want from our big data: improved health, higher quality of life, more productivity, more efficiency, etc. What we don’t know is exactly how the data we’ve collected can get us there.
Right now, running queries on data, or put simply, asking questions, is an expensive, time consuming process that requires significant manpower. In the same way that scientists need to write proposals and apply for grants, you need to provide ample proof that the query you’re running is justified. But unlike scientists, your explanation can’t be, “we’re curious to see if we’re right or wrong about this.” You’ve got to show how this question will improve your business, save money, grow revenue and beat the competition. That puts you in a bit of a Catch-22. How can you be confident that the question you're asking is the right one, if you're not allowed the trial and error process that weeds out the wrong ones?
Probably the biggest question on everyone’s mind right now is: when is the reality of big data going to live up to the hype? The answer: As soon as we have the freedom to ask the dumb questions that will ultimately make us smarter. The next question is: how do we get there? According to our CTO Jason Hoffman (and we know we’re a little biased, but we really think he’s right) the solution lies in the democratization of big data. That means making it cheaper to ask questions, processing questions more quickly and ensuring that anyone at your company, not just the guy with a PhD in data science, can ask them.
If we’re being honest with ourselves, we don’t know yet really know just how big big data can be. Finding out means allowing more people to ask more questions. Even the dumb ones.