It takes a team: Collaboration and workflow in open data science

Data science is a team activity. Ideally, you want to build a team in which diverse specialists pool their skills and knowledge, wield a core set of sophisticated productivity tools and collaborate flexibly and efficiently. Data scientists produce a steady stream of machine-learning, predictive, segmentation and other advanced analytics models. As a team, its effectiveness depends on having advanced tools such as Apache Spark and languages such as R and Python at their disposal. It also depends on having tools to support creative design, agile collaboration and workflow management of data, algorithms, models and other artifacts.