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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Developing Code for Data Processing using Python and SQL | 22% | - Use Databricks-specific libraries and APIs - Write efficient and maintainable code - Implement complex data processing logic |
| Data Ingestion & Acquisition | 7% | - Ingest data from diverse sources - Use Auto Loader and structured streaming - Handle incremental and batch data loads |
| Cost & Performance Optimisation | 13% | - Improve query and pipeline performance - Apply cost management best practices - Optimize compute and storage resources |
| Data Governance | 7% | - Enforce data policies and standards - Manage data assets and metadata - Use Unity Catalog for governance |
| Data Modelling | 6% | - Optimize table design and partitioning - Design Medallion Architecture - Implement dimensional and relational models |
| Data Sharing and Federation | 5% | - Manage cross-platform data access - Implement Lakehouse Federation - Use Delta Sharing for secure data sharing |
| Monitoring and Alerting | 10% | - Set up alerts and notifications - Monitor pipeline performance and health - Track data lineage and metrics |
| Data Transformation, Cleansing, and Quality | 10% | - Implement schema evolution and management - Apply data cleansing and validation rules - Enforce data quality standards |
| Debugging and Deploying | 10% | - Implement CI/CD and DevOps practices - Troubleshoot and debug pipelines - Deploy using Asset Bundles, CLI, and APIs |
| Ensuring Data Security and Compliance | 10% | - Implement access control and permissions - Secure data at rest and in transit - Ensure data privacy and compliance |
Databricks Certified Data Engineer Professional Sample Questions:
Question 1
A data engineering team is setting up deployment automation. To deploy workspace assets remotely using the Databricks CLI command, they must configure it with proper authentication.
Which authentication approach will provide the highest level of security?
A. Use a service principal and its Personal Access Token.
B. Use a shared user account and its OAuth client secret.
C. Use a service principal with OAuth token federation.
D. Use a service principal ID and its OAuth client secret.
Question 2
What statement is true regarding the retention of job run history?
A. It is retained for 60 days, after which logs are archived
B. It is retained for 60 days, during which you can export notebook run results to HTML
C. It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3
D. It is retained until you export or delete job run logs
E. It is retained for 90 days or until the run-id is re-used through custom run configuration
Question 3
The following table consists of items found in user carts within an e-commerce website.
The following MERGE statement is used to update this table using an updates view, with schema evolution enabled on this table.
How would the following update be handled?
A. The new nested field is added to the target schema, and files underlying existing records are updated to include NULL values for the new field.
B. The update throws an error because changes to existing columns in the target schema are not supported.
C. The new restored field is added to the target schema, and dynamically read as NULL for existing unmatched records.
D. The update is moved to separate ''restored'' column because it is missing a column expected in the target schema.
Question 4
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 itv columns will be returned; the email column will contain all null values.
C. Only the email and ltv columns will be returned; the email column will contain the string
"REDACTED" in each row.
D. The email, age. and ltv columns will be returned with the values in user ltv.
E. Three columns will be returned, but one column will be named "redacted" and contain only null values.
Question 5
A data engineer is designing an append-only pipeline that needs to handle both batch and streaming data in Delta Lake. The team wants to ensure that the streaming component can efficiently track which data has already been processed. Which configuration should be set to enable this?
A. overwriteSchema
B. mergeSchema
C. checkpointLocation
D. partitionBy
Solutions:
| Question 1 Answer: C | Question 2 Answer: B | Question 3 Answer: A | Question 4 Answer: C | Question 5 Answer: C |
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