It isn’t easy building a data science team that can agilely deal with the demands of businesses in today’s data-centric world. Big data is more pervasive and easier to accumulate than ever, and new machine learning tools that help sort through it seem to pop up daily.
As data scientists find themselves reporting to a larger variety of departments, the profession is becoming “hard to define,” according to Peter Krensky, a senior research analyst at Gartner. Speaking in a recent webinar from the research and advisory firm, entitled “The Essentials of Data Science and Machine Learning,” Krensky offered several tips on building a data science team for the modern world.
Author: Mark Labbe