Databricks Utilities help combine different tasks in a single notebook, like file operations with ETL tasks.
They are available in Python, Scala, and R cells but not in SQL cells.
Databricks continuously releases utilities, with some in preview and others in general availability.
Common Utilities:
File System Utilities: Access the Databricks file system and perform file operations.
Secrets Utilities: Retrieve secret values stored in secret scopes (Databricks or Azure Key Vault).
Widget Utilities: Parameterize notebooks for reusable, dynamic workflows.
Notebook Workflow Utilities: Chain notebooks together for organized workflows.
Example workflows include mounting Azure Data Lake containers, retrieving secrets, passing parameters, and chaining notebooks.
The dbutils package provides flexibility, integrating with Python, Scala, or R, unlike the %fs magic command, which is more suitable for ad-hoc queries.
File System Operations can be accessed via dbutils.fs.ls, providing Python list outputs for deeper manipulation, such as filtering folders or files.
Help for Databricks Utilities is available using dbutils.help() and dbutils.fs.help('method') for specific methods.
In the next lessons, File System Utilities will be used for mounting, and Secret Utilities will be leveraged for secure data access.

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