The rapid evolution of analytics has put a wonderful array of cutting-edge technologies at fingertips, from Spark and Kafka to TensorFlow and Scikit-Learn. And yet, despite this technological treasure trove, the vast majority of big data projects fail, according to analyst firms. So what gives?
It’s likely a combination of factors, but one that stands out is that we spend too much time focusing on technology and not enough on business process, industry experts say. Gartner analyst Nick Heudecker turned some heads last year when he said 85% of big data projects were failures, citing poor integration with existing business process, as well as internal policies, executive buy-in, lack of skills, and the ever-present security-governance issue.
Author: Alex Woodie