Biases in how data are collected, a lack of context, gaps in what’s gathered, artifacts of how data are processed and the overall cognitive biases that lead even the best researchers to see patterns where there are none mean that “we may be getting drawn into particular kinds of algorithmic illusions,” said MIT Media Lab visiting scholar Kate Crawford. In other words, even if you have big data, it’s not something that Joe in the IT department can tackle—it may require someone with a PhD, or the equivalent amount of experience. And when they’re done, their answer to your problem might be that you don’t need “big data” at all.