Demand for analytics and data science talent shows no signs of abating, and training and up-skilling existing resources from within remains challenging.
Will "democratization" and "citizen data scientists" come to the rescue?
"Citizen data scientists" using no-code, drag-and-drop tools are promised as the solution. However, this approach fails to meet the needs of enterprise data science at scale. Why?
Organizations need to reimagine their analytics and data science talent strategy, focusing on developing talent from within on a common platform using code-first tools alongside their expert data scientists.
That’s why Domino Data Lab and AWS worked with David Stodder, Senior Director of Business Intelligence at TDWI, to identify five key plays to scaling data science through a code-first strategy.