There is a clear overlap between business intelligence and predictive analytics, I view BI as an affiliate of PA as they share so much in common: they use the same data, often use similar metrics and even sometimes utilize the same tools.
Business intelligence is the world of descriptive analytics: reflective analysis that provides a clear view into the business—reporting on what has happened and what is currently happening.
Predictive analytics is forward-looking analysis: providing future insights into the business—predicting what is likely to happen and why it’s likely to happen.
Business intelligence looks for trends at the macro-level of the business, and then drills up, down, or across the data to identify areas of under-and over-performance. Areas may include: time, products, customers, partners, campaigns, or other business dimensions.
Predictive analytics, on the other hand, builds analytic models at the fundamental level of the business—at the individual customer, product, campaign, store, and device levels—and looks for predictable behaviors, and business rules that can be used to predict the likelihood of certain behaviors, actions, and outcomes.
Be that as it may, my final point is that BI and PA are important but complementary disciplines. BI is a much larger field and understandably so. PA is more of a specialty, but a specialty that is gaining visibility and recognition as an important skill set to have in any organization. Here’s to further collaboration in the future!
