Data analysis is the key to drive business decisions through answering abstract business questions but it’s hard to get right
13 hours ago
“We have observed a drop in our core metric, what is going on?”
“What are the drivers for churn?”
As data scientists, we encounter questions like these every day. A stakeholder comes across something they want to understand better, and they look to us to take an open-ended question like this and make sense of it.
However, even seasoned data scientists are sometimes stunned by just how vague or open-ended these questions are. As a result, they don’t know where to start or how to carry these analyses forward.
In fact, a lot of analyses either circle high level at 30,000 feet and only scratch the surface, or get stuck in a rabbit hole that’s very far from the original question we hoped to answer.
Like mentioned at the beginning, there are generally two categories of open-ended business questions data scientists encounter:
- Questions that are more investigative and aim to identify drivers of a past event; most companies/people refer to this as root cause analysis (e.g. “XX metrics decreased week over week, what…