最新のCertified-Data-Engineer-Professional問題集で試験を準備する

Databricks Certified-Data-Engineer-Professional 試験概要:

Databricks Certified-Data-Engineer-Professional 試験シラバストピック:

Databricks Certified Data Engineer Professional 認定 Certified-Data-Engineer-Professional 試験問題：

問題 #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. 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.
B. 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.
C. 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.
D. Because databases on Databricks are merely a logical construct, choices around database organization do not impact security or discoverability in the Lakehouse.
E. Working in the default Databricks database provides the greatest security when working with managed tables, as these will be created in the DBFS root.

問題 #2

A data engineer created a daily batch ingestion pipeline using a cluster with the latest DBR version to store banking transaction data, and persisted it in a MANAGED DELTA table called prod.gold.all_banking_transactions_daily. The data engineer is constantly receiving complaints from business users who query this table ad hoc through a SQL Serverless Warehouse about poor query performance. Upon analysis, the data engineer identified that these users frequently use high- cardinality columns as filters. The engineer now seeks to implement a data layout optimization technique that is incremental, easy to maintain, and can evolve over time. Which command should the data engineer implement?

A. Alter the table to use Liquid Clustering and implement a periodic OPTIMIZE command.
B. Alter the table to use Hive-Style Partitions and implement a periodic OPTIMIZE command.
C. Alter the table to use Hive-Style Partitions + Z-ORDER and implement a periodic OPTIMIZE command.
D. Alter the table to use Z-ORDER and implement a periodic OPTIMIZE command.

問題 #3

A workspace admin has created a new catalog called finance_data and wants to delegate permission management to a finance team lead without giving them full admin rights. Which privilege should be granted to the finance team lead?

A. GRANT OPTION privilege on the finance_data catalog.
B. ALL PRIVILEGES on the finance_data catalog.
C. Make the finance team lead a metastore admin.
D. MANAGE privilege on the finance_data catalog.

問題 #4

A data engineer needs to implement column masking for a sensitive column in a Unity Catalog- managed table. The masking logic must dynamically check if users belong to specific groups defined in a separate table (group_access) that maps groups to allowed departments. Which approach should the engineer use to efficiently enforce this requirement?

A. Create a UDF that hardcodes allowed groups and apply it as a column mask.
B. Apply a column mask that references the group_access mapping table in its UDF.
C. Create a view without selecting the sensitive column.
D. Use a row filter to restrict access based on the user's group.

問題 #5

A table named user_ltv is being used to create a view that will be used by data analysts on various teams. Users in the workspace are configured into groups, which are used for setting up data access using ACLs.
The user_ltv table has the following schema:
email STRING, age INT, ltv INT
The following view definition is executed:

An analyst who is not a member of the marketing group executes the following query:
SELECT * FROM email_ltv
Which statement describes the results returned by this query?

A. The email and ltv columns will be returned with the values in user itv.
B. Only the email and ltv columns will be returned; the email column will contain the string
"REDACTED" in each row.
C. The email, age. and ltv columns will be returned with the values in user ltv.
D. Only the email and itv columns will be returned; the email column will contain all null values.
E. Three columns will be returned, but one column will be named "redacted" and contain only null values.

解説：