Data Acquisition and Understanding: ingest data and determine if it can answer the presenting question (effectively combines Data Understanding and Data Cleaning from CRISP-DM).

Business Understanding: define objectives and identify data sources.

TDSP Life Cycle Team Data Science Lifecycle (Based on Microsoft, 2020)Īlthough the lifecycle graphic looks quite different, TDSP’s project lifecycle is like CRISP-DM and includes five iterative stages:

If you are interested in learning how to use TDSP and other frameworks to deliver data science projects, explore the Data Science Team Lead course. It comes as no surprise that these two often leverage Microsoft Azure however, a team could use other tech stacks and still adhere to TDSP.

Recommended infrastructure and resources.This is a modern data science process that combines elements of the core data science life cycle, software engineering, and Agile processes. Launched in 2016, TDSP is “an agile, iterative data science methodology to deliver predictive analytics solutions and intelligent applications efficiently.” ( Microsoft, 2020 ). If you combine Scrum and CRISP-DM, you would get something that looks like Microsoft’s Team Data Science Process.

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