Why data analytics initiatives still fail

As companies seek to move beyond basic business intelligence to predictive and prescriptive analytics as well as machine learning and artificial intelligence, they need increasing levels of expertise on their data teams. That in turn has shined a spotlight on the data scientist position. But equally important is the data engineer, who wrangles all the data sets that need to come together for data scientists to do their work but has (so far) gained less attention in many organizations.

That’s been changing, says Lori Sherer, a partner with Bain & Company.

“We’ve seen the growth in the demand for data engineer is about 2x the growth in the demand for data scientist,” Sherer says.