Precognition, the ability to see events in the future, has always fascinated humankind. We probably will get there someday, but time series forecasting gets you close. The human brain is naturally trained to anticipate future events by analyzing the past, but the brain often makes only linear predictions because it can't analyze the amount of data generated in a modern enterprise. How about letting a machine record those past sequences of events from millions of sources, analyze the data, and make predictions for your business? Let's take for example a software as a service (SaaS) provider that has thousands of customers from different industries, including online retail, oil and gas, and airline.

From the earliest days of my career, data, and the insights that we draw from that data, have always held a special place in my heart. At a company like Amazon, getting millions of items delivered to customers on demanding timeframes, and running massive world-wide data centers to host our cloud-based service offerings are all dependent on our ability to understand, process, and analyze vast quantities of data. This is of course true in almost every industry – the ability to leverage data can be the difference between your business thriving or dying. As a technology leader, what concerns me about this is that many companies aren't investing in the right kind of technologies that will enable them to be successful here. Take for example databases, many are still using traditional relational databases for everything, simply because they don't know any other way.