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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

Databricks Certified Data Engineer Professional Sample Questions:

1. A healthcare analytics team is implementing a dimensional model in Delta Lake for patient care analysis. They have a date dimension table and are evaluating design options to ensure it supports a wide range of time-based analyses. Which design approach for the date dimension will support efficient time-based querying and aggregation?

A) Store the date as string in ISO format (YYYY-MM-DD) for readability.
B) Pre-calculate attributes like fiscal_period, quarter, month_name, day_of_week, and holiday.
C) Store only the date value and calculate all time attributes in queries.
D) Create separate dimension tables for different calendar systems (fiscal, academic, etc.)

2. A data engineer is configuring a pipeline that will potentially see late-arriving, duplicate records.
In addition to de-duplicating records within the batch, which of the following approaches allows the data engineer to deduplicate data against previously processed records as it is inserted into a Delta table?

A) Perform an insert-only merge with a matching condition on a unique key.
B) Rely on Delta Lake schema enforcement to prevent duplicate records.
C) VACUUM the Delta table after each batch completes.
D) Set the configuration delta.deduplicate = true.
E) Perform a full outer join on a unique key and overwrite existing data.

3. A data engineer has configured their Databricks Asset Bundle with multiple targets in databricks.yml and deployed it to the production workspace. Now, to validate the deployment, they need to invoke a job named my_project_job specifically within the prod target context.
Assuming the job is already deployed, they need to trigger its execution while ensuring the target- specific configuration is respected. Which command will trigger the job execution?

A) databricks execute my_project_job -e prod
B) databricks job run my_project_job --env prod
C) databricks bundle run my_project_job -t prod
D) databricks run my_project_job -t prod

4. Which statement describes a key benefit of an end-to-end test?

A) It provides testing coverage for all code paths and branches.
B) It pinpoint errors in the building blocks of your application.
C) It makes it easier to automate your test suite
D) It closely simulates real world usage of your application.

5. Which statement regarding spark configuration on the Databricks platform is true?

A) Spark configuration set within an notebook will affect all SparkSession attached to the same interactive cluster
B) Spark configuration properties can only be set for an interactive cluster by creating a global init script.
C) Spark configuration properties set for an interactive cluster with the Clusters UI will impact all notebooks attached to that cluster.
D) The Databricks REST API can be used to modify the Spark configuration properties for an interactive cluster without interrupting jobs.
E) When the same spar configuration property is set for an interactive to the same interactive cluster.

Solutions: