Predictive analytics tells you what will happen; prescriptive analytics tells you what to do about it.
Predictive analytics predates big data, of course, but the two complement each other nicely. According to Gartner, more than 30% of analytics projects by 2015 will provide insights based on structured and unstructured data.
Being tipped off to the future is always helpful, but what’s the best course of action once you get a prediction? That’s where prescriptive analytics comes into play. An emerging technology that goes beyond descriptive and predictive analytics, prescriptive tools recommend specific courses of action and show the likely outcome of each decision.
To its proponents, prescriptive analytics is the next evolution in business analytics, an automated system that combines big data, business rules, mathematical models and machine learning to deliver sage advice in a timely fashion.
One of these proponents is Ayata, an Austin, Texas, developer of prescriptive analytics software. The company began as a research and development effort 10 years ago in Toronto, Canada, and incorporated in 2009. Its customers today include such major tech players as Cisco, Dell and Microsoft.