n every state but New Jersey, I can go to a gas station and fill up my own tank whenever I need to. Ideally self-service analytics works the same way. Business users who need data can get it themselves without help from a dedicated technician. But just because I can pump gas doesn’t mean I know how to refine oil or set up a gas station. While an element of self-service exists, other specialists have created the infrastructure and laid the groundwork, so I can get what I need quickly and move on.

One reason self-service analytics is so hard is that it means different things to different people. For example, an executive might think self-service analytics is the ability to view an online dashboard during an operational review meeting. A manager, on the other hand, views it as the ability to drill, sort, and filter dashboards and reports. And a marketing analyst thinks it’s about creating custom data sets from corporate and demographic data. With self-service analytics, one size does not fit all. To successfully deploy self-service analytics, organizations must tailor the analytics experience to each and every individual in an organization.

Self-service analytics requires an intricate dance that blends user empowerment and corporate governance. Balancing these dueling forces requires a business-driven, federated organization, a refined user classification model, agile governance processes, and enlightened leadership.