Agile

Scaling a Model with Data Driven Scrum at Lely

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The following is an interview by Jeff Saltz with Jelle de Jong. Jelle, a certified DSPA Team Lead, is an independent consultant. He currently works with Lely, an agricultural business based in the Netherlands. Jeff: Can you provide some background on your consulting business? Jelle: I’ve been in the quantitative modeling industry for 15+ years. […]

Agile

10 Data Science Project Metrics

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Measuring Data Science Project Performance

Ironically, data science teams that are so intensely focused on model measurement often don’t measure their own project performance which is problematic because… …But wait! Data scientists measure all sorts of metrics. Of course, they will closely monitor data science metrics and KPIs such as RMSE, F1 scores, or correlation coefficients. Such metrics are critical […]

Agile

Data Driven Agile With Data Driven Scrum

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Data Driven Scrum

When teams try to have a data driven agile approach, they often try to use an existing framework, such as Scrum or Kanban. Yet, there are key challenges teams have in leveraging these frameworks. Therefore, the Data Science Process Alliance created an alternative framework called Data Driven Scrum which is designed with data science in […]

Agile

Vertical vs Horizontal Slicing Data Science Deliverables

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layered cake

Traditional software approaches favor developing software layer-by-layer (horizontal slicing) while software agilists strive to deliver software by thin end-to-end value streams (vertical slicing). …but what makes sense for data science? Consider a churn project… Imagine that you are tasked to pro-actively minimize customer churn at a telecom company. The retention department has requested the following […]

Agile

Is Agile a Fit for Data Science?

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Agile Gazelle

As explained in the previous post, much of the debate on agile’s potential fit for data science focuses on the use of a specific framework (such as Scrum), and the associated processes and artifacts such as story pointing, burn down charts, or sprint lengths. Unfortunately, this drowns the argument into details that ignore agile for […]

Agile

5 Agile Data Science Myths

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Agile data science myths

One of the most common questions of data science project management is some variation of: “Is agile a fit for data science?” Unfortunately – like a lot of questions in data science – this question itself is often misunderstood. Many (if not most) blog posts, on-line forums, and conversations debate this question by evaluating specific […]