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 […]


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 […]


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CRISP-DM Life cycle

What is CRISP DM? The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that naturally describes the data science life cycle. It’s like a set of guardrails to help you plan, organize, and implement your data science (or machine learning) project. Business understanding – What does the business need? Data understanding – What data do we have / […]

Traditional Approaches

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Ad hoc processes might work for smaller, one-off projects but are becoming less sustainable as data science matures into a team sport. Meanwhile, Waterfall is the classic highly-structured project management approach that dates back to antiquity and was common in software 10 – 20 years ago. Realizing the need for a process specific to data […]