Over the past several years, several companies have adopted self-service analytics stacks to enable business users to ask and answer questions using data, thereby freeing data scientists to focus on other objectives. In this post, Stancil calls into question the utility of self-service analytics tools by demonstrating that analysis is a skill that data scientists and analysts cultivate through training. Even armed with self-serve tools, business users cannot answer complex questions without this skill set. He concludes that the promise of self-service analytics can be most effectively delivered by identifying a set of key metrics that non-analysts can explore while empowering data teams to respond efficiently to other requests.