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rstudio::conf 2018 case study
Agile data science
March 4, 2018
Agile development is a well-established practice for modern software development that gained broad adoption as software became ubiquitous in the business world. As data science matures in the organization, perhaps we are at a similar crossroads. What can data science learn from the agile approach? I'll share my experience as a data scientist in an agile product development group – what agile practices have proven most valuable, how R has enabled an agile approach, and where data science may need its own set of agile principles.
VP of Data Science at The Looma Project
Elaine works at the intersection of data science and business, leading the company to take full advantage of data as part of their analytics-driven, film-based storytelling platform. This includes data strategy, data infrastructure, reporting, and delivery of predictive analytics.
