Wheelings & Dealings: Apigee Acquires InsightsOne for Big Data Analytics

Apigee, a company focusing on API management, has announced that is has acquired InsightsOne, a big data predictive analytics firm, according to TechCrunch.

“Success in today’s mobile-first digital world requires a single vision that spans and connects business and technology,” Apigee CEO Chet Kapoor said in a statement. “In this new world, the business intelligence and context gleaned through the massive amount of big data available about customers, products, developers – every part of a digital business – must be tightly integrated with technology infrastructure to effect real change. InsightsOne dramatically expands Apigee’s big data predictive analytics capabilities, and we welcome the accomplished InsightsOne team to Apigee.”

With InsightsOne, customers will be able to not only store massive amounts of data, but make predictions about what customers will do before they do it using complex statistical processes. Meteorologists also use modeling to predict the weather, but InsightsOne and Apigee will make the process available to more businesses.

“Predictive is the ‘killer app’ for big data, and Apigee is the only company that delivers predictive analytics with API and app infrastructure in an integrated platform,” InsightsOne CEO Waqar Hasan said. “InsightsOne is a natural fit for Apigee, expanding its big data analytics to make all customer interactions smarter and more effective. We are thrilled to be joining Apigee as the company helps businesses – including many of the world’s largest companies – transform into leaders in the new digital world.”

One example Apigee used is predicting which patients will complain about their healthcare, so providers could reach out to them before they do.

With an API, developers can implement powerful analytics without having to develop their own systems. They’ll just be able to make a library call and then spend their time making their own applications.

The growth of predictive analytics will also drive the adoption of new database models. One of them will be graph databases, which draw on an area of mathematics known as graph theory. The various data points are known as “nodes” and the connections between them are known as “edges.” A good example of a graph would be an airline network, where the destinations an airline flies to are nodes, and the actual flights are edges.

Big data analytics will require models like graphs that show relationships rather than the standard relational databases like SQL that simply organize data into tables. Hence the migration of graph theory from a computer science discrete mathematics course into the real world.