Your company has a team of developers. The team creates Python libraries of reusable code that is used to transform data. You create a Fabric workspace name Workspace1 that will be used to develop…

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Explanation

This question tests knowledge of Microsoft Fabric's Environment-based library management, specifically how to make custom Python libraries available by default to all new notebooks in a workspace. The correct approach uses a Fabric Environment item configured as the workspace default.

Approach. The correct three-action sequence is: (1) Create a new Environment item inside Workspace1, (2) Upload the custom Python library files (.whl or .py) into that Environment and publish it, then (3) Open Workspace1 Settings and set that Environment as the workspace default environment. Once set as the default, every new notebook created in Workspace1 automatically attaches to this environment, making the libraries available without any per-notebook configuration. This is the designated Fabric mechanism for workspace-wide, reusable dependency management - it replaces the older Spark pool-level library approach used in Azure Synapse.

Concept tested. Microsoft Fabric Workspace Environment configuration - specifically, creating a Fabric Environment, adding custom Python libraries to it, and designating it as the workspace-level default so new notebooks inherit those libraries automatically. This falls under the Fabric Data Engineering / Spark compute management domain.

Reference. Microsoft Learn: 'Create, configure, and use an environment in Microsoft Fabric' and 'Manage Apache Spark libraries in Microsoft Fabric' (learn.microsoft.com/fabric/data-engineering/environment-manage-library)

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