Imagine pulling into a shopping mall parking lot and getting a special offer that entices you to visit a particular store. Or that you are browsing in a department inside a store you’ve visited before and get personalized service from a salesperson that has been informed of your buying history and expected purchases through a mobile device.
Or it could be that you are about to leave the store because you’ve found a better price online and you get a “We’ll beat any price” offer delivered to your smartphone—just before you walk out of the door. This is today’s reality. This is real-time!
In today’s businesses, having the right information at the right time is crucial when making important business decisions. Reports and information that would previously take days to receive through a batch process are now available in mere seconds, along with informed and actionable insights. Real-time is NOW! Real-time big data analytics generate insights or recommendations to drive business value at the point of sale. Innovative technologies like SAP HANA enable near-instantaneous analysis of large data sets. Combining real-time big data analytics with mobile technologies will enable retailers to reach out to consumers and influence their behavior based on their immediate context.
The truth is retail or e-commerce businesses aren’t the only businesses that can benefit from real-time analytics. Other examples could be material procurement at a manufacturing unit or selling an idea on a social media site. Incorporating continuous analytics enables companies to maintain a global view of fast-changing data sets and quickly respond to significant patterns and trends. Conventional big data analytics systems have not been well suited for analyzing fast-changing, operational data. But this is all changing. “In-memory analytics and complex processing” like those provided by SAP HANA have the capability to analyze data in real-time and extract intelligence on the fly.
Big Data today has become a true platform for strategic business opportunities. What started as traditional business intelligence batch reporting has now turned into real-time insight and operational business intelligence. It is now well on its way from insight into foresight. Dynamic couponing, responsive design, recommendation engines, real-time attrition alerter, manufacturing chain optimization or even Machine-to-Machine (M2M) in the Internet of Things (IoT) are all use cases that prove that the time is now for real-time.