Research and Development

Posted on
managing data science projects with the research and development life cycle

What is a Data Science R&D Approach? The data science process can be viewed as a research endeavor that transitions into an engineering project. As such, some organizations combine traditional research methodologies with modern agile development approaches. Google Brain and DemandJump are two companies that split data science into these two general buckets. Training on […]

Bimodal: Agile-Waterfall

Posted on
data science bimodal project management

What is Agile-Waterfall? Agilists juxtapose waterfall as the antithesis of agility. However, Eric Stolterman, Senior Executive Associate Dean at Indiana University, believes that crystalline processes such as waterfall and liquid processes such as Scrum should simultaneously co-exist. The same problem can be viewed from the lenses of both crystalline or liquid processes, “similar to the […]

Hybrid Approaches

Posted on

Hybrid Data Science Approaches Without well-known, comprehensive project management approaches specific for data science, teams often combine elements from two or more approaches to cater to their own needs. Although combining multiple approaches can be challenging, they allow users to design approaches that fit their individual needs. Two common hybrid approaches in data science are: […]