Modern data analytics involves two major areas of effort. First, it strives to automate all of the efforts that have gone into collecting, storing, integrating, organizing, cleaning, validating, and analyzing data. Second, it mandates cultivating the skills, habits, processes, and culture so people can easily use this data to find actionable insights, and implement them.
Oh, and ideally, we want to do all of this in real-time. When an interesting event happens, we want to know everything we can about it, what it means, and what to do about it – to either trigger an automated response or flag it for human intervention.
Actually, it may be better to show a state-of-the-art example of real-time data analysis rather than try to explain it. In this video, Dilip Kamar, VP for Amazon Go, details the numerous technologies that went into creating cashier-less Amazon Go convenience stores. The same technology was very recently rolled out into a pilot for two Whole Foods supermarket stores.
TLDR; Every time a customer picks up a product is an event that gets analyzed in real-time and sets off a chain of reactions. Lots of sensors, facial recognition, an absolute need for accuracy of product and price, all feeding supply chain decisions.