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Databricks Certified-Data-Engineer-Professional Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Streaming Workloads and Change Data Capture | ~11% | - Apply AUTO CDC APIs and exactly-once semantics - Implement reliable streaming pipelines |
| Topic 2: Monitoring, Logging, and Troubleshooting | ~8% | - Use Spark UI, Query Profiler, and system tables - Diagnose common pipeline and job failures |
| Topic 3: Data Modeling | ~10% | - Design scalable Delta Lake schemas and clustering - Apply dimensional modeling techniques |
| Topic 4: CI/CD, Testing, and Deployment | ~6% | - Implement testing and deployment pipelines - Deploy with Declarative Automation Bundles, CLI, and REST API |
| Topic 5: Data Transformation, Cleansing, and Quality | ~12% | - Enforce data quality and quarantine bad data - Apply advanced Spark transformations |
| Topic 6: Data Sharing and Federation | ~8% | - Configure Delta Sharing and Lakehouse Federation |
| Topic 7: Cost and Performance Optimization | ~13% | - Optimize queries, clusters, and storage - Leverage system tables and observability tools |
| Topic 8: Developing Code for Data Processing using Python and SQL | ~22% | - Implement scalable Python/SQL code and project structures - Build pipelines with Lakeflow Spark Declarative Pipelines and Auto Loader - Manage dependencies, libraries, and UDFs |
| Topic 9: Security and Governance | ~10% | - Implement row-level security, column masking, and compliance - Manage Unity Catalog permissions and ACLs |
Databricks Certified Data Engineer Professional Sample Questions:
Question 1
A Delta table of weather records is partitioned by date and has the below schema:
date DATE, device_id INT, temp FLOAT, latitude FLOAT, longitude FLOAT
To find all the records from within the Arctic Circle, you execute a query with the below filter:
latitude > 66.3
Which statement describes how the Delta engine identifies which files to load?
A. All records are cached to an operational database and then the filter is applied
B. The Hive metastore is scanned for min and max statistics for the latitude column
C. All records are cached to attached storage and then the filter is applied
D. The Delta log is scanned for min and max statistics for the latitude column
E. The Parquet file footers are scanned for min and max statistics for the latitude column
Question 2
A Data Engineer is building a fraud detection pipeline that calls out to Open AI, via a Python library, and needs to include an access token when using the API. Which Databricks CLI command should the Data Engineer use to create the secret?
A. databricks secrets put-secret KEY SCOPE; dbutils.secrets.get (KEY, SCOPE)
B. databricks tokens put-token KEY SCOPE; dbutils.secrets.get (KEY, SCOPE)
C. databricks secrets put-secret SCOPE KEY; dbutils.secrets.get (SCOPE, KEY)
D. databricks tokens put-token SCOPE KEY; dbutils.tokens.get (SCOPE, KEY)
Question 3
A data engineer is running a groupBy aggregation on a massive user activity log grouped by user_id. A few users have millions of records, causing task skew and long runtimes. Which technique will fix the skew in this aggregation?
A. Use salting by adding a random prefix to skewed keys before aggregation, then aggregate again after removing the prefix.
B. Filter out the skewed users before the aggregation.
C. Increase the Spark driver memory and retry.
D. Use reduceByKey instead of groupBy to avoid shuffles.
Question 4
Predictive Optimization is an automated Databricks service enabled by default for Unity Catalog Managed tables. It helps maintain Delta tables by continuously optimizing them to ensure optimal performance and costs. Which two operations does Predictive Optimization run to maintain the Delta tables? (Choose two.)
A. PARTITION BY
B. ANALYZE
C. COMPACT
D. BUCKETING
E. OPTIMIZE
Question 5
When a new Databricks project starts, the central IP team provisions the required infrastructure using Terraform and a Service Principal. This includes creating a Databricks workspace, a Unity Catalog linked to an External Location, and a Databricks group containing all project team members. Project teams must store all assets - e.g., tables and volumes, as Managed assets in Unity Catalog. This model hides infrastructure complexity while giving teams autonomy within their catalog. They can create and manage schemas, tables, volumes, and related objects but cannot rename, delete, or change catalog permissions, those remain under IT's control. Which rights should the project group be granted to enable this model?
A. The group needs to have ALL PRIVILEGES and the MANAGE on the catalog.
B. The group should be made OWNER of the catalog.
C. The group needs to have ALL PRIVILEGES on the catalog.
D. The group needs to have USE CATALOG and USE SCHEMA on the catalog.
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: A | Question 4 Answer: B,E | Question 5 Answer: D |
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