If you're in any way involved in the world of analytics, you're probably familiar with the notion of self-service: giving everyone direct access to even the most advanced analytics functionalities. But even the companies with the best data management skills haven't quite achieved this dream yet. There is no tool powerful enough to enable non-expert users to manipulate data as if they were experts.

Yet the promise is seductive: to give business teams greater autonomy and free up IT and analytics departments. This is especially true given that businesses need to take ownership of their data in order to make the right decisions in real-life situations. But is complete self-service possible, or even advisable?

In reality, it depends on the meaning of the word “self-service”: there are different levels of self-service, some riskier than others. The key is to allow users to feel comfortable enough with their analytics tools so they turn to them whenever they need them.

With this ebook, you'll discover the problems that self-service could solve in your organization, and the best ways to get there without putting your data at risk. In particular, you'll learn to distinguish between the 4 levels of self-service: