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

Section	Weight	Objectives
Topic 1: Data Sharing and Federation	5%	- Manage cross-platform data access - Implement Lakehouse Federation - Use Delta Sharing for secure data sharing
Topic 2: Ensuring Data Security and Compliance	10%	- Implement access control and permissions - Ensure data privacy and compliance - Secure data at rest and in transit
Topic 3: Monitoring and Alerting	10%	- Monitor pipeline performance and health - Set up alerts and notifications - Track data lineage and metrics
Topic 4: Data Transformation, Cleansing, and Quality	10%	- Apply data cleansing and validation rules - Enforce data quality standards - Implement schema evolution and management
Topic 5: Data Governance	7%	- Enforce data policies and standards - Manage data assets and metadata - Use Unity Catalog for governance
Topic 6: Debugging and Deploying	10%	- Deploy using Asset Bundles, CLI, and APIs - Troubleshoot and debug pipelines - Implement CI/CD and DevOps practices
Topic 7: Data Ingestion & Acquisition	7%	- Ingest data from diverse sources - Handle incremental and batch data loads - Use Auto Loader and structured streaming
Topic 8: Data Modelling	6%	- Implement dimensional and relational models - Optimize table design and partitioning - Design Medallion Architecture
Topic 9: Cost & Performance Optimisation	13%	- Improve query and pipeline performance - Optimize compute and storage resources - Apply cost management best practices
Topic 10: Developing Code for Data Processing using Python and SQL	22%	- Implement complex data processing logic - Use Databricks-specific libraries and APIs - Write efficient and maintainable code

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q24-Q29):

NEW QUESTION # 24
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 auditing group executes the following query:
SELECT * FROM user_ltv_no_minors
Which statement describes the results returned by this query?

A. All columns will be displayed normally for those records that have an age greater than 17; records not meeting this condition will be omitted.
B. All age values less than 18 will be returned as null values all other columns will be returned with the values in user_ltv.
C. All values for the age column will be returned as null values, all other columns will be returned with the values in user_ltv.
D. All columns will be displayed normally for those records that have an age greater than 18; records not meeting this condition will be omitted.
E. All records from all columns will be displayed with the values in user_ltv.

Answer: D

Explanation:
Given the CASE statement in the view definition, the result set for a user not in the auditing group would be constrained by the ELSE condition, which filters out records based on age. Therefore, the view will return all columns normally for records with an age greater than 18, as users who are not in the auditing group will not satisfy the is_member('auditing') condition. Records not meeting the age > 18 condition will not be displayed.

NEW QUESTION # 25
The data engineering team has configured a job to process customer requests to be forgotten (have their data deleted). All user data that needs to be deleted is stored in Delta Lake tables using default table settings.
The team has decided to process all deletions from the previous week as a batch job at 1am each Sunday. The total duration of this job is less than one hour. Every Monday at 3am, a batch job executes a series of VACUUM commands on all Delta Lake tables throughout the organization.
The compliance officer has recently learned about Delta Lake's time travel functionality. They are concerned that this might allow continued access to deleted data.
Assuming all delete logic is correctly implemented, which statement correctly addresses this concern?

A. Because the vacuum command permanently deletes all files containing deleted records, deleted records may be accessible with time travel for around 24 hours.
B. Because the default data retention threshold is 7 days, data files containing deleted records will be retained until the vacuum job is run 8 days later.Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
C. Because the default data retention threshold is 24 hours, data files containing deleted records will be retained until the vacuum job is run the following day.
D. Because Delta Lake time travel provides full access to the entire history of a table, deleted records can always be recreated by users with full admin privileges.
E. Because Delta Lake's delete statements have ACID guarantees, deleted records will be permanently purged from all storage systems as soon as a delete job completes.

Answer: B

Explanation:
https://learn.microsoft.com/en-us/azure/databricks/delta/vacuum

NEW QUESTION # 26
A data architect is implementing Delta Sharing as part of their data governance strategy to enable secure data collaboration with external partners and internal business units. The architect must establish a permission framework that allows designated data stewards to create shares for their respective domains while maintaining security boundaries and audit compliance. Which specific permissions and roles must be assigned to enable users to create, configure, and manage Delta Shares while maintaining proper security governance and access controls?

A. Any user with USE_CATALOG privilege can create shares
B. Users need the MANAGE SHARES permission on the workspace
C. Users need to be metastore admins or have CREATE SHARE privilege for the metastore
D. Only workspace admins can create and manage shares

Answer: C

Explanation:
Creating and managing Delta Shares requires elevated governance privileges at the metastore level. Assigning users as metastore admins or granting them the CREATE SHARE privilege allows designated data stewards to create and configure shares within defined security boundaries, while preserving centralized auditability and access control.

NEW QUESTION # 27
A view is registered with the following code:

Both users and orders are Delta Lake tables.
Which statement describes the results of querying recent_orders?

A. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
B. Results will be computed and cached when the view is defined; these cached results will incrementally update as new records are inserted into source tables.
C. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
D. All logic will execute when the view is defined and store the result of joining tables to the DBFS; this stored data will be returned when the view is queried.

Answer: A

NEW QUESTION # 28
A data engineering workspace was automatically enabled for Unity Catalog, creating a workspace catalog. New team members report they can create tables in the default schema but cannot access table in other schemas within the same workspace catalog. Why are the new team members unable to access tables in other schemas?

A. Workspace users receive USE CATALOG and specific privileges on default schema only.
B. New users only receive CREATE TABLE privileges on the default schema.
C. Tables in other schemas require additional BROWSEprivileges that new users don't receive automatically
D. Workspace catalog permissions are not subject to inheritance rules.

Answer: A

Explanation:
When a workspace catalog is automatically created, new users are granted USE CATALOG and limited privileges on the default schema only. Access to other schemas requires explicit grants, so users cannot see or query tables in those schemas without additional permissions.

NEW QUESTION # 29
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