Big data is measured by volume, velocity, and variety. My colleague and fellow big data lover Mansour Raad recently highlighted how these three measures themselves are increasing almost exponentially in today’s sensored world while talking at one of the commercial business special interest groups (SIGs) during the Esri User Conference (UC).
We no longer store and batch process data. Today, everything is in a stream—a misnomer when we consider the tidal wave of data. We have also become living, breathing, walking, talking sensors thanks to our smart phones and Fitbit-like devices that track us as we are active, eating, and even our sleep.
Doing Business in the Internet of Everything
We are living in the Internet of Everything (IoE) because of this continuous data stream. In the business world every consumer action can be recorded. The instant an item is pulled from a shelf, we know if you keep that item, or put it back on the shelf, how many items were picked up, and how many were purchased, when, and where. Many stores have sensors in the floors to understand customer walk patterns, promotion effectiveness, linger time, and hotspots.
All this information is fuel for predictive analytics. We are now in the age of learning algorithms which auto-pilot themselves through the oceans of data and parameters in big data and provide insights which companies could not discover in other ways.
Geographic relationships can now be parametrized, so we can easily ask questions that help us gain real knowledge about customers as consumers and their habits and needs.
Geography Makes Sense of the Barrage of Business Data
One example I came across recently exemplifies how location—the context in which all things are connected based on where they are—is changing business. A retailer is using “feels-like” temperatures to look at different beverage purchasing patterns by geography and segmentation.
Regional patterns based on differences in how consumers experience the weather and their perception drive different choices in drinks with the same actual temperature. Big data is being used to identify these patterns and differentiate between say, Chicago and Atlanta to merchandize stores and develop forward looking, proactive marketing campaigns based on past experience. Different day temperatures, time of year, consumer origin, local events; all these complicating factors can be understood much better by learning from geography. “The algorithm” has learned its geography lesson and is now able to apply it.
Again, to paraphrase Mansour, yes, batch was good—but streams, fed through geographic pattern analysis, and the ability to learn in real-time, is more important. Are you ready for the wave of big data to redirect your business?