Workflow

What is a Data Science Workflow?

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A data science workflow defines the phases (or steps) in a data science project. Using a well-defined data science workflow is useful in that it provides a simple way to remind all data science team members of the work to be done to do a data science project. One way to think about the benefit […]

Coordination Framework

3 Steps to Define a Data Science Process

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How do you effectively define a data science process? Conceptually, a data science process explains and defines how a team should execute a project. Having a robust, repeatable process helps to ensure that the project efficiently and effectively delivers actionable insight. In this article, I’ll explore how to create a well-defined data science process in […]

Team

CRISP-DM for Data Science Teams: 5 Actions to Consider

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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 […]

Team

8 Key Data Science Team Roles

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Based on my personal experience, below are the 8 key data science team 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 […]

Team

10 Data Science Ethics Questions

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Data Science Ethics

Integrating Ethics in a Data Science Project: 10 Questions a Data Science Project Team Should Ask While the potential ethical issues that might arise when using data science and artificial intelligence have certainly been in the popular press recently, there is not been as much discussion with respect to how a data science team should […]

Agile

Agile Data Science With Data Driven Scrum

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Data Driven Scrum

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. […]