Last Updated: Jul 23, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Data Quality and Governance | 12% | - Governance - Data Lineage - Data Quality |
| Data Processing | 28% | - Structured Streaming - ETL Pipelines - Data Transformation - Spark SQL |
| Data Modeling and Storage | 20% | - File Formats - Storage Optimization - Data Modeling |
| Databricks Lakehouse Platform | 24% | - Data Management - Delta Lake - Lakehouse Architecture - Unity Catalog |
| Monitoring and Troubleshooting | 16% | - Monitoring - Performance Optimization - Troubleshooting |
1. A transactions table has been liquid clustered on the columns product_id, user_id, and event_date. Which operation lacks support for cluster on write?
A) INSERT INTO operations
B) spark.writestream.format('delta').mode('append')
C) spark.write.format('delta').mode('append')
D) CTAS and RTAS statements
2. A distributed team of data analysts share computing resources on an interactive cluster with autoscaling configured. In order to better manage costs and query throughput, the workspace administrator is hoping to evaluate whether cluster upscaling is caused by many concurrent users or resource-intensive queries.
In which location can one review the timeline for cluster resizing events?
A) Ganglia
B) Executor's log file
C) Workspace audit logs
D) Driver's log file
E) Cluster Event Log
3. A healthcare analytics team is implementing a dimensional model in Delta Lake for patient care analysis. They have a date dimension table and are evaluating design options to ensure it supports a wide range of time-based analyses. Which design approach for the date dimension will support efficient time-based querying and aggregation?
A) Create separate dimension tables for different calendar systems (fiscal, academic, etc.)
B) Pre-calculate attributes like fiscal_period, quarter, month_name, day_of_week, and holiday.
C) Store only the date value and calculate all time attributes in queries.
D) Store the date as string in ISO format (YYYY-MM-DD) for readability.
4. A view is registered with the following code:
Both users and orders are Delta Lake tables.
Which statement describes the results of querying recent_orders?
A) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
B) All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
C) The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
D) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
5. 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) Shuffle Hash Joins are always more efficient than Sort Merge Joins.
B) The queries against the Delta Lake tables were able to leverage the dynamic file pruning optimization.
C) Delta Lake enables data skipping and file pruning using a vectorized Parquet reader.
D) The queries against the ORC tables leveraged the dynamic data skipping optimization but not the dynamic file pruning optimization.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: E | Question # 3 Answer: B | Question # 4 Answer: D | Question # 5 Answer: C |
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