There’s a significant gulf between collecting Big Data and being able to confidently act upon it. In that gulf you’ll find data scientists developing and refining models, identifying questions, and communicating the insights and predictions that emerge. Effectively conveying these conclusions requires more than simply plotting points on a graph or map: it’s a narrative process. D.J. Patil of Greylock Partners emphasized this during a talk last week at LeWeb conference in Paris, noting that “data science is about creating narratives. It is about creating analogies, about using complex data to tell stories.”
Contrary to the stereotype of the lab coat-clab researcher wholly beholden to objective fact, Patil argued that the value of Data Science lies in untangling subjective areas where ambiguity reigns. “Everyone right now is regimented into this idea that a data scientist is a statistician and a math person, very cold, very regimented,” he said. He compared the work of data scientists to that of journalists, adding, “Subjective areas are where data science shines. It allows us to ask questions. Data allows you to ask questions—it facilitates a conversation. The point is to have a debate.”
Patil’s points about the role of narrative and storytelling in data science echo the thoughts of other leading practitioners in the field, such as Hans Rosling and Stamen’s Eric Rodenbeck. Check out the video of Patil’s talk below, and more takeaways from the Wall Street Journal and ZDNet.
About the AuthorMore Content by Paul M. Davis