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Databricks Certified-Data-Engineer-Professional Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Modelling | - Scalable Data Models
|
| Topic 2: Ensuring Data Security and Compliance | - Data Security
|
| Topic 3: Cost & Performance Optimisation | - Cost Optimization
|
| Topic 4: Developing Code for Data Processing using Python and SQL | - Using Python and Tools for Development
|
| Topic 5: Monitoring and Alerting | - Monitoring
|
| Topic 6: Debugging and Deploying | - Deploying CI/CD
|
| Topic 7: Data Governance | - Metadata and Discoverability
|
| Topic 8: Data Ingestion & Acquisition | - Design and implement data ingestion pipelines
|
| Topic 9: Data Sharing and Federation | - Lakehouse Federation
|
| Topic 10: Data Transformation, Cleansing, and Quality | - Data Quality
|
Databricks Certified Data Engineer Professional Sample Questions:
Question 1
A data engineer is creating a daily reporting job. There are two reporting notebooks--one for weekdays and one for weekends. An "if/else condition" task is configured as
{{job.start_time.is_weekday}} == true to route the job to either the weekday or weekend notebook tasks. The same job would be used across multiple time zones. Which action should a senior data engineer take upon reviewing the job to merge or reject the pull request?
A. Reject, as they should use {{job.trigger_time.is_weekday}} instead.
B. Reject, as the {{job.start_time.is_weekday}} is not a valid value reference.
C. Reject, as the {{job.start_time.is_weekday}} is for the UTC timezone.
D. Merge, as the job configuration looks good.
Question 2
The data engineer is using Spark's MEMORY_ONLY storage level. Which indicators should the data engineer look for in the spark UI's Storage tab to signal that a cached table is not performing optimally?
A. Size on Disk is < Size in Memory
B. The RDD Block Name included the '' annotation signaling failure to cache
C. Size on Disk is> 0
D. On Heap Memory Usage is within 75% of off Heap Memory usage
E. The number of Cached Partitions> the number of Spark Partitions
Question 3
The data governance team is reviewing user for deleting records for compliance with GDPR. The following logic has been implemented to propagate deleted requests from the user_lookup table to the user aggregate table.
Assuming that user_id is a unique identifying key and that all users have requested deletion have been removed from the user_lookup table, which statement describes whether successfully executing the above logic guarantees that the records to be deleted from the user_aggregates table are no longer accessible and why?
A. No; the change data feed only tracks inserts and updates not deleted records.
B. No; files containing deleted records may still be accessible with time travel until a BACUM command is used to remove invalidated data files.
C. Yes; Delta Lake ACID guarantees provide assurance that the DELETE command successed fully and permanently purged these records.
D. Yes; the change data feed uses foreign keys to ensure delete consistency throughout the Lakehouse.
E. No; the Delta Lake DELETE command only provides ACID guarantees when combined with the MERGE INTO command
Question 4
Which distribution does Databricks support for installing custom Python code packages?
A. sbt
B. Wheels
C. nom
D. CRAM
E. jars
F. CRAN
Question 5
A data engineer is testing a collection of mathematical functions, one of which calculates the area under a curve as described by another function.
assert(myIntegrate(lambda x: x*x, 0, 3) [0] == 9)
Which kind of the test does the above line exemplify?
A. functional
B. Integration
C. Unit
D. End-to-end
E. Manual
Solutions:
| Question 1 Answer: C | Question 2 Answer: C | Question 3 Answer: B | Question 4 Answer: C | Question 5 Answer: C |
