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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Modeling | ~10% | - Design scalable Delta Lake schemas and clustering - Apply dimensional modeling techniques |
| Topic 2: Streaming Workloads and Change Data Capture | ~11% | - Apply AUTO CDC APIs and exactly-once semantics - Implement reliable streaming pipelines |
| Topic 3: Developing Code for Data Processing using Python and SQL | ~22% | - Build pipelines with Lakeflow Spark Declarative Pipelines and Auto Loader - Implement scalable Python/SQL code and project structures - Manage dependencies, libraries, and UDFs |
| Topic 4: Security and Governance | ~10% | - Implement row-level security, column masking, and compliance - Manage Unity Catalog permissions and ACLs |
| Topic 5: Data Transformation, Cleansing, and Quality | ~12% | - Enforce data quality and quarantine bad data - Apply advanced Spark transformations |
| Topic 6: Cost and Performance Optimization | ~13% | - Leverage system tables and observability tools - Optimize queries, clusters, and storage |
| Topic 7: CI/CD, Testing, and Deployment | ~6% | - Deploy with Declarative Automation Bundles, CLI, and REST API - Implement testing and deployment pipelines |
| Topic 8: Data Sharing and Federation | ~8% | - Configure Delta Sharing and Lakehouse Federation |
| Topic 9: Monitoring, Logging, and Troubleshooting | ~8% | - Diagnose common pipeline and job failures - Use Spark UI, Query Profiler, and system tables |
A data engineer and a platform engineer are working together to automate their system tasks. A script needs to be executed outside of Databricks only if a particular daily Databricks job finishes successfully for the day. Databricks CLI command was used to check the last execution of the job. What are the required command options for that task?
Correct Answer: B 🗳️
Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).
A team of data engineer are adding tables to a DLT pipeline that contain repetitive expectations for many of the same data quality checks.
One member of the team suggests reusing these data quality rules across all tables defined for this pipeline.
What approach would allow them to do this?
Correct Answer: D 🗳️
Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).
A data engineer wants to join a stream of advertisement impressions (when an ad was shown) with another stream of user clicks on advertisements to correlate when impressions led to monetizable clicks.
In the code below, Impressions is a streaming DataFrame with a watermark ("event_time", "10 minutes")
The data engineer notices the query slowing down significantly.
Which solution would improve the performance?
Correct Answer: D 🗳️
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?
Correct Answer: B 🗳️
Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).
When scheduling Structured Streaming jobs for production, which configuration automatically recovers from query failures and keeps costs low?
Correct Answer: B 🗳️
Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).
1 Customer ReviewsCustomers Feedback (* Some similar or old comments have been hidden.)All the questions provided were a part of the certified Certified-Data-Engineer-Professional exam. Thanks to the PrepAwayTest team for such updated material. I scored 90% marks.
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