Within the enterprise tech space, the seemingly endless evolution of data-driven insights continues apace-but when will it end?

(When data is no longer useful, so, never.)

In previous columns, I discussed the transformation of the decision support systems of yesteryear to today's analytics platforms. The latest expansion in 2020 is powered by artificial intelligence, or at least is labeled as such. In reality, it is machine learning-a branch of AI that delivers the majority of current AI use cases-that has brought forth an increasingly popular term: augmented analytics.

The industry is keen on putting new words in front of analytics-business, data, edge, distributed, real-time-and I am as guilty as the next analyst for giving into this temptation. But I will defend the use of augmented analytics (even if I didn't come up with it) because it is critical for enterprises to become genuinely data-driven.