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Databricks Certified Data Engineer Professional Sample Questions:

1. The data engineering team is migrating an enterprise system with thousands of tables and views into the Lakehouse. They plan to implement the target architecture using a series of bronze, silver, and gold tables. Bronze tables will almost exclusively be used by production data engineering workloads, while silver tables will be used to support both data engineering and machine learning workloads. Gold tables will largely serve business intelligence and reporting purposes. While personal identifying information (PII) exists in all tiers of data, pseudonymization and anonymization rules are in place for all data at the silver and gold levels.
The organization is interested in reducing security concerns while maximizing the ability to collaborate across diverse teams.
Which statement exemplifies best practices for implementing this system?

A) Because databases on Databricks are merely a logical construct, choices around database organization do not impact security or discoverability in the Lakehouse.
B) Working in the default Databricks database provides the greatest security when working with managed tables, as these will be created in the DBFS root.
C) Storinq all production tables in a single database provides a unified view of all data assets available throughout the Lakehouse, simplifying discoverability by granting all users view privileges on this database.
D) Isolating tables in separate databases based on data quality tiers allows for easy permissions management through database ACLs and allows physical separation of default storage locations for managed tables.
E) Because all tables must live in the same storage containers used for the database they're created in, organizations should be prepared to create between dozens and thousands of databases depending on their data isolation requirements.

2. A data engineer wants to reflector the following DLT code, which includes multiple definition with very similar code:

In an attempt to programmatically create these tables using a parameterized table definition, the data engineer writes the following code.

The pipeline runs an update with this refactored code, but generates a different DAG showing incorrect configuration values for tables.
How can the data engineer fix this?

A) Convert the list of configuration values to a dictionary of table settings, using table names as keys.
B) Load the configuration values for these tables from a separate file, located at a path provided by a pipeline parameter.
C) Convert the list of configuration values to a dictionary of table settings, using different input the for loop.
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
D) Wrap the loop inside another table definition, using generalized names and properties to replace with those from the inner table

3. All records from an Apache Kafka producer are being ingested into a single Delta Lake table with the following schema:
key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG There are 5 unique topics being ingested. Only the "registration" topic contains Personal Identifiable Information (PII). The company wishes to restrict access to PII. The company also wishes to only retain records containing PII in this table for 14 days after initial ingestion.
However, for non-PII information, it would like to retain these records indefinitely.
Which of the following solutions meets the requirements?

A) Data should be partitioned by the registration field, allowing ACLs and delete statements to be set for the PII directory.
B) All data should be deleted biweekly; Delta Lake's time travel functionality should be leveraged to maintain a history of non-PII information.
C) Because the value field is stored as binary data, this information is not considered PII and no special precautions should be taken.
D) Separate object storage containers should be specified based on the partition field, allowing isolation at the storage level.
E) Data should be partitioned by the topic field, allowing ACLs and delete statements to leverage partition boundaries.

4. The data architect has mandated that all tables in the Lakehouse should be configured as external Delta Lake tables.
Which approach will ensure that this requirement is met?

A) When tables are created, make sure that the external keyword is used in the create table statement.
B) Whenever a database is being created, make sure that the location keyword is used Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
C) Whenever a table is being created, make sure that the location keyword is used.
D) When configuring an external data warehouse for all table storage. leverage Databricks for all ELT.
E) When the workspace is being configured, make sure that external cloud object storage has been mounted.

5. A Spark job is taking longer than expected. Using the Spark UI, a data engineer notes that the Min, Median, and Max Durations for tasks in a particular stage show the minimum and median time to complete a task as roughly the same, but the max duration for a task to be roughly 100 times as long as the minimum.
Which situation is causing increased duration of the overall job?

A) Credential validation errors while pulling data from an external system.
B) Task queueing resulting from improper thread pool assignment.
C) Spill resulting from attached volume storage being too small.
D) Network latency due to some cluster nodes being in different regions from the source data
E) Skew caused by more data being assigned to a subset of spark-partitions.

Solutions: