You have to have a well-honed sense of irony if you work in the world of data analytics and Artificial Intelligence (AI). So many situations evolve counter to the way they’re supposed to. Take the unlikely role that commercial AI vendors are now playing in the democratization of AI and Machine Learning (ML). See, open source was supposed to make advanced technologies available without the interference of those money-grubbing commercial AI vendors. “Power to the (tech) people!” Well, not so much, it turns out.

Gartner recently published its report, “Top 10 Data and Analytics Technology Trends That Will Change Your Business.” As the authors of the report note: “These data and analytics technology trends will have significant disruptive potential over the next three to five years.” Augmented data analytics emerges as one of the key trends highlighted in the report. This article is intended to help you gain a better understanding of this important trend in data analytics.

Professor Leonard Schlesinger of the Harvard Business School, considered one of America’s foremost experts on customer service, had one of his greatest moments of insight while waiting in a grocery checkout line. As he waited with his full basket, he watched customers breezing through the express line. He wondered, “Why is the store punishing me, making me wait for a long time with my $300 cart, while people spending $3 get the royal treatment?” It seemed the store wasn’t analyzing customer data and didn’t know their customers. To Schlesinger, the issue had to do with a misalignment of customer service and customer prioritization. The supermarket couldn’t identify its best customers.