Exam Databricks-Machine-Learning-Associate Topic 2 Question 37 Discussion

Actual exam question for Databricks's Databricks-Machine-Learning-Associate exam
Question #: 37
Topic #: 2
A new data scientist has started working on an existing machine learning project. The project is a scheduled Job that retrains every day. The project currently exists in a Repo in Databricks. The data scientist has been tasked with improving the feature engineering of the pipeline's preprocessing stage. The data scientist wants to make necessary updates to the code that can be easily adopted into the project without changing what is being run each day.
Which approach should the data scientist take to complete this task?

Suggested Answer: A Vote an answer

The best approach for the data scientist to take in this scenario is to create a new branch in Databricks, commit their changes, and push those changes to the Git provider. This approach allows the data scientist to make updates and improvements to the feature engineering part of the preprocessing pipeline without affecting the main codebase that runs daily. By creating a new branch, they can work on their changes in isolation. Once the changes are ready and tested, they can be merged back into the main branch through a pull request, ensuring a smooth integration process and allowing for code review and collaboration with other team members.
Reference:
Databricks documentation on Git integration: Databricks Repos

by Aaron at May 10, 2026, 02:33 PM

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