Team

Data Analyst vs Data Scientist

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data analyst vs data scientist

As organizations continue to expand their data analysis competencies, the data science function is becoming more of a team sport with numerous team roles within the data science group. Of all these roles, the difference between the data analyst and data scientist role is perhaps the most confusing. Indeed, the roles have similar responsibilities. Data […]

Workflow

What is a Data Science Life Cycle?

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data science life cycle

A data science life cycle is an iterative set of steps you take to deliver a data science project or product. Because every data science project and team are different, every specific data science life cycle is different. However, most data science projects tend to flow through the same general life cycle. With help from […]

Team

How to Lead Data Science Teams

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leading data science teams

It’s an understatement that great leadership is challenging and rare. And leading data science teams has unique challenges: Stakeholders might get disillusioned by your team’s inability to deliver magic The battle to recruit and retain data science talent is fierce Data science’s ethical dilemmas are particularly perplexing There is not an agreed-upon process for managing […]

Team

Data Science vs Software Engineering

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data scientist venn diagram

The battle between Data Science vs Software Engineering isn’t really a battle. Rather these are two somewhat overlapping and complementary fields that are similar in many ways. However, dig deeper, and you’ll find key differences: Data science is more exploratory. Software engineers are more focused on systems building. And data science project management should be […]

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.

Team

The Rise of Data Science Project Management

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Sunrise

It is ironic that data science, a field built upon rigorous scientific methodologies, has been slow to adopt much rigor from project management approaches. Rather, in data science, project management tends to be ad hoc and is often on the back-burner as a secondary consideration to technologies and algorithms. Fortunately, this is changing as organizations […]

Team

10 Reasons You Need a Data Science Product Manager

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Data Science Product Manager

Unlike more tactical roles like the project manager who oversees the project life cycle or a process master who drives effective processes, the product manager is more strategic. Wearing many different hats, this product person researches market needs, defines how to map the solution to the problem space, and sets the product vision. Evolving from […]