Can you mix and match elements of multiple project management approaches? Of course! This post explores two such general hybrid approaches for data science:agile-waterfall and research and development.
Similarities of Data Science and Research Efforts In many ways, a data science project looks like a research project, in that both require significant effort exploring a problem that typically doesn’t have a known answer. For example, in data science, it’s often not clear where there is “value in the data”, which is similar to […]
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 […]
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: Bimodal, also known as […]