DP-600 Maintain a Data Analytics Solution Practice Question
A Lakehouse in your Fabric environment has grown significantly over time, and you notice that query performance on the Delta tables is decreasing. You also want to minimize storage costs by removing older versions of data files that are no longer needed for 'Time Travel'. Which maintenance strategy should you implement?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Schedule a notebook to run 'OPTIMIZE' followed by 'VACUUM' on the tables.
Regular maintenance of Delta tables is essential for both performance and cost management in Microsoft Fabric. The OPTIMIZE command improves data layout for faster reads, while the VACUUM command removes obsolete files. Together, these operations keep the Lakehouse efficient by ensuring that only necessary, well-structured data is retained and processed during queries, preventing 'file sprawl' in the underlying storage.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Run a Spark notebook that executes the 'REORG' command on all tables.
Why it's wrong here
The 'REORG' command is a concept from traditional relational databases like SQL Server or DB2 and does not exist as a native Delta Lake command for Lakehouse maintenance in Microsoft Fabric. Using incorrect terminology or commands from other systems will result in script errors and will not achieve the desired optimization of the Parquet-based Delta tables.
- ✓
Schedule a notebook to run 'OPTIMIZE' followed by 'VACUUM' on the tables.
Why this is correct
This is the standard maintenance pattern for Delta tables. 'OPTIMIZE' consolidates small files into larger ones to speed up reads, and 'VACUUM' deletes files that are older than a specific retention period (default 7 days). This combination addresses both the performance degradation caused by many small files and the increased storage costs from excessive historical data versions.
- ✗
Enable the 'Auto-shrink' property in the Lakehouse settings to manage storage.
Why it's wrong here
Microsoft Fabric Lakehouses do not have an 'Auto-shrink' property. Storage in Fabric is based on OneLake, which is built on Azure Data Lake Storage Gen2. Management of file versions and storage optimization must be handled explicitly through Delta Lake commands like VACUUM, as the system does not automatically delete old file versions without a defined retention policy and command.
- ✗
Delete the Lakehouse and recreate it from the original data sources weekly.
Why it's wrong here
Deleting and recreating a Lakehouse is an extreme and inefficient approach that causes significant downtime for all downstream reports and users. It also loses all historical metadata and requires re-running all ingestion pipelines, which consumes unnecessary capacity units. It is much better to perform incremental maintenance using native Delta Lake commands that preserve availability and logic.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This DP-600 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-600 exam.