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

Section	Weight	Objectives
Topic 1: Data Transformation, Cleansing, and Quality	10%	- Handling missing or inconsistent data - Standardization and normalization - Data validation and quality checks
Topic 2: Debugging and Deploying	10%	- CI/CD and DevOps practices - Deployment using bundles, CLI, and APIs - Troubleshooting pipelines and errors
Topic 3: Data Governance	7%	- Policy enforcement - Data lineage and metadata tracking - Unity Catalog management
Topic 4: Monitoring and Alerting	10%	- Pipeline observability and logging - Performance and health monitoring - Setting up alerts and notifications
Topic 5: Ensuring Data Security and Compliance	10%	- Data encryption and masking - Compliance standards implementation - Access control and permissions
Topic 6: Developing Code for Data Processing using Python and SQL	22%	- Data transformation and aggregation - Batch and incremental processing logic - Integration with Databricks APIs and tools
Topic 7: Data Ingestion & Acquisition	7%	- Schema inference and evolution - Auto Loader and streaming ingestion - Connecting to diverse data sources
Topic 8: Cost & Performance Optimisation	13%	- Storage optimization (partitioning, Z-order, indexing) - Cluster configuration and scaling - Query optimization and caching
Topic 9: Data Modelling	6%	- Medallion Architecture implementation - Delta Lake table design - Schema design and management
Topic 10: Data Sharing and Federation	5%	- Unity Catalog data sharing - Cross-workspace and cross-cloud access

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Databricks Certified Professional Data Engineer Exam Sample Questions (Q179-Q184):

NEW QUESTION # 179
Which of the following command can be used to drop a managed delta table and the underlying files in the storage?

A. DROP TABLE table_name INCLUDE_FILES
B. Use DROP TABLE table_name command and manually delete files using com-mand dbutils.fs.rm("/path",True)
C. DROP TABLE table and run VACUUM command
D. DROP TABLE table_name
E. DROP TABLE table_name CASCADE

Answer: D

Explanation:
Explanation
The answer is DROP TABLE table_name,
When a managed table is dropped, the table definition is dropped from metastore and everything including data, metadata, and history are also dropped from storage.

NEW QUESTION # 180
A Delta Lake table was created with the below query:

Consider the following query:
DROP TABLE prod.sales_by_store -
If this statement is executed by a workspace admin, which result will occur?

A. An error will occur because Delta Lake prevents the deletion of production data.
B. The table will be removed from the catalog but the data will remain in storage.
C. Data will be marked as deleted but still recoverable with Time Travel.
D. The table will be removed from the catalog and the data will be deleted.
E. Nothing will occur until a COMMIT command is executed.

Answer: D

Explanation:
When a table is dropped in Delta Lake, the table is removed from the catalog and the data is deleted. This is because Delta Lake is a transactional storage layer that provides ACID guarantees. When a table is dropped, the transaction log is updated to reflect the deletion of the table and the data is deleted from the underlying storage. References:
* https://docs.databricks.com/delta/quick-start.html#drop-a-table
* https://docs.databricks.com/delta/delta-batch.html#drop-table

NEW QUESTION # 181
A data engineering team is migrating off its legacy Hadoop platform. As part of the process, they are evaluating storage formats for performance comparison. The legacy platform uses ORC and RCFile formats.
After converting a subset of data to Delta Lake , they noticed significantly better query performance. Upon investigation, they discovered that queries reading from Delta tables leveraged a Shuffle Hash Join , whereas queries on legacy formats used Sort Merge Joins . The queries reading Delta Lake data also scanned less data.
Which reason could be attributed to the difference in query performance?

A. Delta Lake enables data skipping and file pruning using a vectorized Parquet reader.
B. The queries against the Delta Lake tables were able to leverage the dynamic file pruning optimization.
C. The queries against the ORC tables leveraged the dynamic data skipping optimization but not the dynamic file pruning optimization.
D. Shuffle Hash Joins are always more efficient than Sort Merge Joins.

Answer: A

Explanation:
Delta Lake outperforms legacy Hadoop formats because it leverages Parquet-based storage , data skipping
, and file pruning . According to Databricks documentation, Delta Lake automatically stores detailed statistics (min/max values and file-level metadata) in the transaction log. During query planning, the engine uses these statistics to skip entire files that do not match query filters , a process called data skipping and file pruning . Additionally, Delta uses a vectorized Parquet reader , which reduces I/O and CPU overhead.
Together, these optimizations allow Delta to scan significantly less data and produce more efficient physical query plans (e.g., Shuffle Hash Join instead of Sort Merge Join). The performance gain is due to efficient data skipping, not the inherent superiority of join type.

NEW QUESTION # 182
An analytics team wants to run a short-term experiment in Databricks SQL on the customer transactions Delta table (about 20 billion records) created by the data engineering team. Which strategy should the data engineering team use to ensure minimal downtime and no impact on the ongoing ETL processes?

A. Shallow clone the table for the analytics team.
B. Create a new table for the analytics team using a CTAS statement.
C. Deep clone the table for the analytics team.
D. Give the analytics team direct access to the production table.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
Exact extract: "A shallow clone creates a copy of the metadata that references the source data files; it is fast and inexpensive." Exact extract: "A deep clone copies the data." Exact extract: "Clones provide a point-in-time snapshot for experimentation without impacting the source."

NEW QUESTION # 183
Which of the below commands can be used to drop a DELTA table?

A. DROP TABLE table_name FORMAT DELTA
B. DROP DELTA table_name
C. DROP table_name
D. DROP TABLE table_name

Answer: D

NEW QUESTION # 184
......

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