A machine learning team uses Delta Lake to store training data and MLflow to track experiments. They need to ensure that the data used to train a model can be traced back to the exact version of the training dataset. Which combination of features should they use?

Log the Delta Lake table version in the MLflow run using a parameter.

Register the model in the Model Registry with the dataset name.

Use Delta Lake time travel to query the table at a random timestamp.

Store the entire training dataset in the MLflow artifact store.

DatabricksCertified Machine Learning Professional

Domain 2Objective 1

Model Lifecycle Management MACHINE-LEARNING-PROFESSIONAL Practice Questions (Page 4)

Part of the ML Ops domain, which accounts for 44% of the MACHINE-LEARNING-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~22–35 in this domain), expect 4–7 from this objective — we provide 17 practice questions to prepare you well beyond it. (estimate)

17questions here

4free pages

3concepts

44%of the exam

Questions 16–17

16foundation · easy
Which Databricks feature is primarily used for tracking experiments, logging parameters, metrics, and artifacts during model development?
Select an answer first
17application · medium
A machine learning team uses Delta Lake to store training data and MLflow to track experiments. They need to ensure that the data used to train a model can be traced back to the exact version of the training dataset. Which combination of features should they use?
Select an answer first

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Model Lifecycle Management MACHINE-LEARNING-PROFESSIONAL Practice Questions (Page 4)

Questions 16–17

Which Databricks feature is primarily used for tracking experiments, logging parameters, metrics, and artifacts during model development?

A machine learning team uses Delta Lake to store training data and MLflow to track experiments. They need to ensure that the data used to train a model can be traced back to the exact version of the training dataset. Which combination of features should they use?

Keep studying — ML Ops