Exploring and analyzing data is not at all like pumping your own gas. We should all be grateful that when gas stations made the transition from full service to self service many years ago, they did not relegate auto repair to the realm of self service as well. Pumping your own gas involves a simple procedure that requires little skill.
Repairing a car, however, requires a great deal of skill and the right tools.
The same is true of data exploration and analysis (i.e., data sensemaking).
Self service has become one the most lucrative marketing campaigns of the last few years in the realms of business intelligence (BI) and analytics, second only to Big Data. Every vendor in the BI and analytics space makes this claim, with perhaps no exception. Self-service data sensemaking, however, is an example of false advertising that’s producing a great deal of harm. How many bad decisions are being made based on specious analytical findings by unskilled people in organizations that accept the self-service myth? More bad decisions than good, I fear.
Describing analytics as “self service” suggests that it doesn’t require skill. Rather, it suggests that the work can be done by merely knowing how to use the software tool that supports “self-service analytics.” Data sensemaking, however, is not something that tools can do for us. Computers are not sentient; they do not possess understanding. Tools can at best assist us by augmenting our thinking skills, if they’re well designed, but most of the so-called self-service BI and analytics tools are not well designed. At best, these dysfunctional tools provide a dangerous illusion of understanding, not the basis on which good decisions can be made.
Some software vendors frame their products as self service out of ignorance: they don’t understand data sensemaking and therefore don’t understand that self service doesn’t apply. To them, data sensemaking really is like pumping your gas.