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A Delta Lake table representing metadata about content from user has the following schema:
user_id LONG, post_text STRING, post_id STRING, longitude FLOAT, latitude FLOAT, post_time TIMESTAMP, date DATE Based on the above schema, which column is a good candidate for partitioning the Delta Table?

• A. Date
• B. Post_id
• C. latitude
• D. User_id
• E. Post_time

A Databricks job has been configured with 3 tasks, each of which is a Databricks notebook. Task A does not depend on other tasks. Tasks B and C run in parallel, with each having a serial dependency on Task A.
If task A fails during a scheduled run, which statement describes the results of this run?

• A. Tasks B and C will attempt to run as configured; any changes made in task A will be rolled back due to task failure.
• B. Because all tasks are managed as a dependency graph, no changes will be committed to the Lakehouse until all tasks have successfully been completed.
• C. Tasks B and C will be skipped; some logic expressed in task A may have been committed before task failure.
• D. Unless all tasks complete successfully, no changes will be committed to the Lakehouse; because task A failed, all commits will be rolled back automatically.
• E. Tasks B and C will be skipped; task A will not commit any changes because of stage failure.

A data team is automating a daily multi-task ETL pipeline in Databricks. The pipeline includes a notebook for ingesting raw data, a Python wheel task for data transformation, and a SQL query to update aggregates. They want to trigger the pipeline programmatically and see previous runs in the GUI. They need to ensure tasks are retried on failure and stakeholders are notified by email if any task fails. Which two approaches will meet these requirements? (Choose two.)

• A. Use the REST API endpoint /jobs/runs/submit to trigger each task individually as separate job runs and implement retries using custom logic in the orchestrator.
• B. Trigger the job programmatically using the Databricks Jobs REST API (/jobs/run-now), the CLI (databricks jobs run-now), or one of the Databricks SDKs.
• C. Create a multi-task job using the UI, Databricks Asset Bundles (DABs), or the Jobs REST API (/jobs/create) with notebook, Python wheel, and SQL tasks. Configure task-level retries and email notifications in the job definition.
• D. Use Databricks Asset Bundles (DABs) to deploy the workflow, then trigger individual tasks directly by referencing each task's notebook or script path in the workspace.
• E. Create a single orchestrator notebook that calls each step with dbutils.notebook.run(), defining a job for that notebook and configuring retries and notifications at the notebook level.

A data team is implementing an append-only Delta Lake pipeline that processes both batch and streaming data. They want to ensure that schema changes in the source data are automatically incorporated without breaking the pipeline. Which configuration should the team use when writing data to the Delta table?

• A. mergeSchema = true
• B. ignoreChanges = false
• C. validateSchema = false
• D. overwriteSchema = true

A platform team lead is responsible for automating the individual teams attribution towards SQL Warehouse usage. The requirement is to identify the SQL warehouse usage at the individual user's level and generate a daily report to be shared with an executive team that includes leaders from all business units. How should the platform lead generate an automated report that can be shared daily?

• A. Use the system tables to capture the audit and billing usage data and share the queries with the executive team. This enables the executives to execute the query and see the latest results any time.
• B. Use the system tables to capture the audit and billing usage data and create a dashboard with daily refresh schedules and shared with the executive team.
• C. Let the users run the SQL query and then directly report the usage to the executives. The ownership of the SQL warehouse usage will be with the individual teams.
• D. Restrict users from running any SQL query unless they provide all the query details so that the attribution can be calculated and shared with the executive team.