As big data crosses the chasm and transitions into mainstream adoption, most uses cases are analytical in nature: understand behavior of customers, perform advanced risk analysis, dramatically increase the volume of data that can be stored or processed.
Predict: In 2014, big data will start to be used for operational purposes and will ultimately be consumed by many applications, apps, and devices.
With big data becoming a true computing platform, insight gathered from big data projects will become available not only to reporting applications and human consumers, but also to a broad variety of consuming systems and devices. In a similar way that its business intelligence “ancestor” went from batch reporting to real-time insight and operational BI, big data is on a path to feed insight (or foresight) into operational uses. Dynamic couponing, recommendation engines, real-time fraud detection, manufacturing chain optimization or even Machine-to-Machine in the Internet of Things are all use cases that will feed from big data to increase efficiency and precision.
The key to big data becoming pervasive is the platform itself. The “Big Data 1.0” platform is primarily an analytical platform. “Big Data 2.0” is (will be) a real-time, operational platform. Now that the technology is becoming available, we’ll start to see concrete use cases.