In this article, I’ll explore how to create a well-defined data science process. Specifically, I’ll explain how a team’s data science process is comprised of (1) a team’s data science life cycle framework (i.e., the team’s data science process workflow), (2) a team’s coordination framework, and (3) the integration of these two frameworks. Data Science […]
While there is no standard process for a team to use when working on a data science project, CRISP-DM (CRoss-Industry Standard Process for Data Mining) is one framework that is often considered for data science projects. Perhaps because of this, there are lots of web sites describing the 6 phases of a CRISP-DM project, and […]
Due to efforts to lower the spread of COVID-19, the vast majority of data science teams are now working remote. Unfortunately, many teams are not used to working remote and so, are not aware of the challenges that need to be considered when working in a remote data science team. Most importantly – teams need […]
Based on my personal experience, below are the 8 key roles to think about when building and leading a data science team. These are not in any specific order, as their importance might vary from one project to another, or from one organization to another. Furthermore, not all roles are required to be done by […]
Exploring how to “do” agile data science
Integrating Ethics in a Data Science Project: 10 Questions a Data Science Project Team Should Ask While the potential ethics issues that might arise when using data science and artificial intelligence has certainly been in the popular press recently, there is not been as much discussion with respect to how a data science team should […]
The Need for a New Agile Framework When teams try to use an agile framework for data science, they often try to use Scrum, Kanban. Below I review the key challenges teams have in leveraging these frameworks have challenges. I also briefly explore a TDSP, which is newer framework already discussed on this web site. […]