Data science is a relatively new concept and many organizations have recently started forming data science teams for different needs. Today, Microsoft announced the Team Data Science Process (TDSP), an agile, iterative, data science methodology to and a set of practices for collaborative data science. TDSP is designed to help organizations fully realize the promise of data science for their business, and addresses issues like the below.
If you are building a data science team but unsure how to make the team productive? Are you concerned that the lack of collaboration or consistent processes could hinder project success? Are you doing too many routine data science tasks manually? Do you face challenges capturing or reusing knowledge from data initiatives across your teams?
TDSP has the following components:
- A data science lifecycle definition.
- A standard project structure, including a well-defined directory hierarchy and a list of output artifacts in a standard document template structure that are stored in a versioned repository.
- A shared and distributed analytics infrastructure.
- Productivity tools and utilities for data scientists. These simplify adherence to the process by automatically producing project artifacts and providing scripts for common tasks such as the creation and management of repositories and shared analytics resources.
Read more about it here.