Citizen data scientists: how to empower your workforce to make data driven decisions

Tim Kraska / MIT

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Abstract: Citizen data scientists (CDS) can significantly boost a firm’s business value and analytics maturity. Thus, it comes at no surprise that nowadays almost every company is looking into new tools to empower their workforce to make data-driven decisions and improve their business processes. But according to Gartner most CDS tools are focused on automated machine learning and ignore that data, people, and processes play a similar important role. Citizen data scientists need an environment that allows them to work together with SMEs and data scientists to collaboratively explore a problem across the entire model development lifecycle. Automated ML tools only impact a small portion of the development lifecycle. In this talk, I will present our findings why many current initiatives to increase the number of Citizen Data Scientist fail, explain why current tools for are still inefficient in fully supporting Citizen Data Scientists, and outline how Visual Data Computing, a technique we developed as part of the DARPA D3M program and recently commercialized by Einblick Analytics, addresses many of these challenges in a complete new way by providing the first truly collaborative analytics platform which combines aspects of a workflow engine (like Alteryx) and a visualization tool (like Tableau) with an infinite collaborative canvas (like Miro or Figma).

Bio: Tim Kraska is an Associate Professor of Electrical Engineering and Computer Science in MIT's Computer Science and Artificial Intelligence Laboratory, co-director of the Data System and AI Lab at MIT (DSAIL@CSAIL), and co-founder of Einblick Analytics. Currently, his research focuses on building systems for machine learning, and using machine learning for systems. Before joining MIT, Tim was an Assistant Professor at Brown, spent time at Google Brain, and was a PostDoc in the AMPLab at UC Berkeley after he got his PhD from ETH Zurich. Tim is a 2017 Alfred P. Sloan Research Fellow in computer science and received several awards including the VLDB Early Career Research Contribution Award, the VMware Systems Research Award, the university-wide Early Career Research Achievement Award at Brown University, an NSF CAREER Award, as well as several best paper and demo awards at VLDB, SIGMOD, and ICDE.