A while ago, Professor Tom Davenport, Fellow with the MIT Center for Digital Business, proclaimed that “data scientist” would be the “sexiest” job in the 21st century. This topic was discussed at The 2014 MIT Sloan CIO Symposium, both during the session moderated by Davenport, “Big Data, Analytics and Insights,” and at one of the Big Data “Birds of a Feather” luncheon tables.
And, while data scientists may be “sexy,” that doesn’t mean they’ll solve all of an organization’s big data problems. According to the panelists during the session and practitioners during the luncheon discussions, there are two challenges faced by companies that are looking for data scientists: first, they are expensive and hard to find; and second a data scientist may not be the only specialist needed to truly understand big data. As one participant pointed out, “While a data scientist has the skills to analyze the data, they may not necessarily have the business insight to ask the right questions of the data.”
Don Taylor, CTO of Benefitfocus and one of the panelists, feels that there are four discrete skill sets and job functions required to really understand big data:
- A ”big data”/storage expert
- A business/subject matter expert
- A math/algorithm/machine learning specialist
- A visualization expert to present the data and the findings
It is highly improbable that one person possesses all these skills. Those organizations that are looking solely to data scientists may find that they are only looking at part of the problem. A better approach is to consider building a multi-disciplinary team to ask the right questions of the data, identify the right data to analyze (regardless of source or type of data), properly query the data, and then understand and present the findings to high-level decision makers.
Not every organization will have the foresight to take a highly strategic approach to analyzing data and, eventually, to becoming a data-driven organization. However, those that do will look at big data projects not only as technology solutions, but also as enablers to becoming a more competitive, highly agile business organization.
Therefore, it’s vital for executives and senior management (even senior project leaders) to understand the skill sets their big data projects require and how best to fill those roles. MIT Sloan’s Executive Education program, Big Data: Making Complex Things Simpler, is one resource to help organizations understand what they need to drive business value from their big data projects.
Tom Davenport is a Fellow with the MIT Center for Digital Business, the President’s Distinguished Professor of Information Technology and Management for Babson College, and a Co-Founder of the International Institute for Analytics. Davenport teaches in MIT Sloan’s upcoming Executive Education program, Big Data: Making Complex Things Simpler, occurring July 9–10, 2014.