A platform team is creating a standardized template for Databricks Asset Bundles to support CI/CD. The template must specify defaults for artifacts, workspace root paths, and a run identity, while allowing a "dev" target to be the default and override specific paths. How should the team use databricks.yml to satisfy these requirements?

• A. Use roots, modules, profiles, actor, and targets; where profiles contain workspace and artifacts defaults and actor sets run identity.
• B. Use bundle, artifacts, workspace, run_as, and targets at the top level; set one target with default:true and override workspace paths or artifacts under that target.
• C. Use deployment, builds, context, identity, and environments; set dev as default environment and override paths under builds.
• D. Use project, packages, environment, identity, and stages; set dev as default stage and override workspace under environment.

The security team is exploring whether or not the Databricks secrets module can be leveraged for connecting to an external database.
After testing the code with all Python variables being defined with strings, they upload the password to the secrets module and configure the correct permissions for the currently active user. They then modify their code to the following (leaving all other variables unchanged).

Which statement describes what will happen when the above code is executed?

• A. The connection to the external table will succeed; the string value of password will be printed in plain text.
• B. The connection to the external table will fail; the string "redacted" will be printed.
• C. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the encoded password will be saved to DBFS.
• D. The connection to the external table will succeed; the string "redacted" will be printed.
• E. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the password will be printed in plain text.

The business intelligence team has a dashboard configured to track various summary metrics for retail stories. This includes total sales for the previous day alongside totals and averages for a variety of time periods. The fields required to populate this dashboard have the following schema:

For Demand forecasting, the Lakehouse contains a validated table of all itemized sales updated incrementally in near real-time. This table named products_per_order, includes the following fields:

Because reporting on long-term sales trends is less volatile, analysts using the new dashboard only require data to be refreshed once daily. Because the dashboard will be queried interactively by many users throughout a normal business day, it should return results quickly and reduce total compute associated with each materialization.
Which solution meets the expectations of the end users while controlling and limiting possible costs?

• A. Populate the dashboard by configuring a nightly batch job to save the required values as a table overwritten with each update.
• B. Configure a webhook to execute an incremental read against products_per_order each time the dashboard is refreshed.
• C. Use the Delta Cache to persists the products_per_order table in memory to quickly the dashboard with each query.
• D. Define a view against the products_per_order table and define the dashboard against this view.
• E. Use Structure Streaming to configure a live dashboard against the products_per_order table within a Databricks notebook.

A junior developer complains that the code in their notebook isn't producing the correct results in the development environment. A shared screenshot reveals that while they're using a notebook versioned with Databricks Repos, they're using a personal branch that contains old logic. The desired branch named dev-2.3.9 is not available from the branch selection dropdown.
Which approach will allow this developer to review the current logic for this notebook?

• A. Use Repos to checkout the dev-2.3.9 branch and auto-resolve conflicts with the current branch
• B. Merge all changes back to the main branch in the remote Git repository and clone the repo again
• C. Use Repos to merge the current branch and the dev-2.3.9 branch, then make a pull request to sync with the remote repository
• D. Use Repos to make a pull request use the Databricks REST API to update the current branch to dev-2.3.9
• E. Use Repos to pull changes from the remote Git repository and select the dev-2.3.9 branch.

A departing platform owner currently holds ownership of multiple catalogs and controls storage credentials and external locations. A data engineer has been asked to ensure continuity: transfer catalog ownership to the platform team group, delegate ongoing privilege management, and retain the ability to receive and share data via Delta Sharing. Which role must be in place to perform these actions across the metastore?

• A. Catalog Owner, because catalog owners can transfer any object in any catalog in the metastore.
• B. Workspace Admin, because workspace admins can transfer ownership of any Unity Catalog object.
• C. Metastore Admin, because metastore admins can transfer ownership and manage privileges across all metastore objects, including shares and recipients.
• D. Account Admin, because account admins can only create metastores but cannot change ownership of catalogs.