Beyond Big Data: Why AI Requires Getting Small Data Right

The allure of capturing as much data as possible is strong. And, now that more businesses are experimenting with machine learning and AI, it’s growing stronger. When you aren’t sure what you may eventually need, might as well capture everything, right? But having more data isn’t always better just ask Equifax. More data also means it gets harder to manage and gain valuable insights, and leverage workable data sets to accomplish specific tasks and achieve the desired outcomes. Discussing big data in the context of AI leads us to ask some serious questions about the future of big data. For data scientists like myself, I wonder whether we need big data as much as some think. In my view, in many cases the answer is “no” and instead of going big, what we really need to be doing is thinking smaller. Here’s why.