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

Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer manages a Unity Catalog table customer_data in schema finance that includes sensitive fields like ssn and credit_score. Intern Group should only see masked values, while Analyst Group should only access rows for their assigned region. The data engineer needs to restrict access based on user role and region without duplicating data. How should the data engineer enforce this security policy?

A) Create dynamic views for each user role and manage access with ACLs.
B) Use Unity Catalog's row filters based on the user roles and column masks based on the region.
C) Create views using current_user() and is_account_group_member() functions, and apply masking logic inside the SQL SELECT clause for each sensitive column.
D) Use Unity Catalog's row filters based on the region and column masks based on user roles.

2. When scheduling Structured Streaming jobs for production, which configuration automatically recovers from query failures and keeps costs low?

A) Cluster: Existing All-Purpose Cluster;
Retries: Unlimited;
Maximum Concurrent Runs: 1
B) Cluster: New Job Cluster;
Retries: Unlimited;
Maximum Concurrent Runs: Unlimited
C) Cluster: Existing All-Purpose Cluster;
Retries: None;
Maximum Concurrent Runs: 1
D) Cluster: Existing All-Purpose Cluster;
Retries: Unlimited;
Maximum Concurrent Runs: 1
E) Cluster: New Job Cluster;
Retries: None;
Maximum Concurrent Runs: 1

3. The data engineering team maintains the following code:

Assuming that this code produces logically correct results and the data in the source table has been de-duplicated and validated, which statement describes what will occur when this code is executed?

A) The gold_customer_lifetime_sales_summary table will be overwritten by aggregated values calculated from all records in the silver_customer_sales table as a batch job.
B) A batch job will update the gold_customer_lifetime_sales_summary table, replacing only those rows that have different values than the current version of the table, using customer_id as the primary key.
C) An incremental job will leverage running information in the state store to update aggregate values in the gold_customer_lifetime_sales_summary table.
D) The silver_customer_sales table will be overwritten by aggregated values calculated from all records in the gold_customer_lifetime_sales_summary table as a batch job.
E) An incremental job will detect if new rows have been written to the silver_customer_sales table; if new rows are detected, all aggregates will be recalculated and used to overwrite the gold_customer_lifetime_sales_summary table.

4. A faulty IoT sensor in a factory reports a temperature of -500, causing the LDP pipeline to fail the expectation, which only allows values between -100 and 200 degrees Celsius. The data engineer would like to further analyze the faulty data to better understand the reason behind this. How should the data engineer resolve the faulty data while ensuring data quality standards are maintained?

A) Fix the pipeline code and implement a quarantine logic to isolate the faulty data before re-running the pipeline.
B) Remove all expectations form the pipeline to prevent any future failures, regardless of data quality.
C) Change the expectation action from fail to warn so that invalid records are included in the output and the pipeline does not fail.
D) Ignore the error and simply re-run the pipeline, as Databricks will automatically skip the problematic record on the next run.

5. Which statement describes the default execution mode for Databricks Auto Loader?

A) Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; new files are incrementally and impotently into the target Delta Lake table.
B) New files are identified by listing the input directory; new files are incrementally and idempotently loaded into the target Delta Lake table.
C) New files are identified by listing the input directory; the target table is materialized by directory querying all valid files in the source directory.
D) Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; the target table is materialized by directly querying all valid files in the source directory.
E) Webhook trigger Databricks job to run anytime new data arrives in a source directory; new data automatically merged into target tables using rules inferred from the data.

Solutions: