The balanced team is an interdisciplinary approach to software development that brings together product management, design and engineering in a single team all focused on the end-result: great software that meets or exceeds customer requirements. Each member brings his or her particular strengths, talents and responsibilities to the team, but the idea is that the team works together in an iterative, agile way to build great software.
One persona or role that has been conspicuously left out of the balanced team approach, however, is the data scientist. That’s a mistake, argues Ian Huston, a data scientists at Pivotal, that enterprises make particularly as they attempt to differentiate themselves through the use of machine learning and analytics. By incorporating the data scientist into the balanced team approach, enterprises are better positioned to successfully develop software that uses data and insights to personalize the customer experience and intelligently automates business processes.
In this episode of Pivotal Insights, host Jeff Kelly and Huston talk about the potential benefits of bringing data scientists into the balanced team, best practices for doing so, and put the myth of the Data Science Unicorn to rest.
Show Notes
- Visit http://pivotal.io/podcasts for show notes and other episodes.
- Download the episode and check us out on SoundCloud, subscribe to the feed directly, or on iTunes to have it automatically downloaded for you.
- Twitter: @jeffreyfkelly and @ianhuston
- Feedback: podcast@pivotal.io
News and Resources
- Blog: Data Science in the Balanced Team at ianhuston.net
- Video: Ian’s presentation Data Science and the Balanced Team from PyCon Ireland 2016
- Slides: Slides from Ian’s Data Science in the Balanced Team presentation at PyCon Ireland 2016
- Slides: Slides from Janice Fraser’s 2015 Balanced Team presentation
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