Coordination Framework

Project Management for Data Analytics

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This post will explore managing analytics projects by focusing on three questions: What is the difference between a data scientist and a data analyst? What is the difference between analytics projects and data science projects? What project management / project coordination framework might be helpful to manage analytics projects? Project Management Training for Data Analytics […]

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 […]

Coordination Framework

10 Ways to Manage a Data Science Project – Part IV: Emerging Approaches

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So are there new emerging approaches that are data science native? Microsoft’s Team Data Science Process (TDSP), Domino Data Lab’s Data Science Life Cycle, and the Data Science Process Alliance’s Data Driven Scrum (DDS) are approaches that are both data science native and agile. There are pros and cons specific to each approach but they share some fundamental principles.

Data Science Process Choices

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Data Science Process Learning Center Most IT project management sites focus on software engineering. To our knowledge, there is no comprehensive guide focused on data science. So gathering information from interviews, our industry experience, and third-party sources, we have developed a project management guide dedicated to data science with the goal to arm practitioners with […]

Scrum for Data Science

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managing data science with scrum

Scrum for Data Science Given Scrum’s popularity with software teams, it’s no surprise that many organizations are turning to Scrum for data science product development. But, Does Scrum work for Data Science? Well…results vary. So we’ll start by defining Scrum, then identify Scrum’s use in data science, evaluate its pros and cons, and finally dive […]