Depth in analytics

We often use terms like "big data" and "analytics" as if we mean the same thing for all applications and uses. That is not true. During one of the presentations at a meeting I attended last week, there was a slide that helped explain some of the major differences along a spectrum.

The presenter discussed three main types of analytics:

1. Descriptive:  What happened and why
2. Predictive:    What could happen
3. Prescriptive:   What will happen

As you can see, analytics starts by describing and reporting about past events. It helps explained what happened and then goes into the number of times specific events occurred and where. Over time, as you build your competency, you start to get into predictive and prescriptive analytics.

In the speaker's opinion, the best organizations are weaving analytics into the fabric of their organization. Data analysis becomes a key part of the basic decision-making and strategy of the organization.

I am a big fan of analytics, but I still think there are issues with this interpretation that require clarification. While I generally agree with the model, I still am unclear about how you decide whether or not you are asking the right questions. You might have tons of data, but if it isn't helping to solve your business issues, it may not be all that valuable.