20+ practice questions focused on Ingest and Transform Data — one of the most tested topics on the Microsoft Fabric Data Engineer Associate exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Ingest and Transform Data PracticeYou are transforming data in a Fabric Notebook using PySpark. You need to handle schema evolution when loading data into a Delta table. Which TWO actions should you perform?
Explanation: To handle schema evolution in a Delta table, you can enable it globally for the Spark session by setting spark.databricks.delta.schema.autoMerge.enabled to true, or you can enable it per-write operation using the DataFrame writer option .option('mergeSchema', 'true'). While either approach works independently, you can select both or either depending on the options provided in typical Microsoft exam formats.
Refer to the exhibit. You are receiving OOM errors in your Fabric Notebook. What is the best way to optimize the memory usage for this task?
Explanation: The explanation discusses data skew, broadcasting, and salting, but the correct answer (B) is about Adaptive Query Execution (AQE). While AQE can help with skew, the explanation should explicitly mention how AQE dynamically coalesces small partitions and optimizes join strategies to prevent OOM errors, rather than focusing on manual techniques like salting.
Which THREE factors should you consider when choosing a partition key for a Delta table in Fabric?
Explanation: The explanation correctly identifies that low cardinality is preferred to avoid small files, but the provided options list 'Cardinality of the column values' (A) as correct without specifying low or high. Furthermore, the explanation mentions 'data type' (D) is a factor, but the explanation text provided does not actually justify why data type is a factor for partitioning, whereas the number of rows (C) is a factor in determining if partitioning is even necessary.
Refer to the exhibit. You have configured a Microsoft Fabric pipeline copy activity to ingest paginated data from a REST API endpoint. During execution, the activity fails intermittently when fetching large pages due to response timeouts. Which parameter should you add to the RestSource definition in the pipeline JSON configuration to resolve pagination timeout issues?
Explanation: The question asks for a parameter to resolve 'response timeouts' during pagination. None of the provided options address timeout settings. The correct parameter for this scenario in a Microsoft Fabric/ADF REST source is 'httpRequestTimeout'. Option B is a configuration for pagination logic, not timeout resolution.
You have a large Delta table in your Fabric Lakehouse. You are observing slow read performance on queries that filter by a specific column. What is the most recommended action to improve query performance?
Explanation: While partitioning is a valid technique, it is not the 'most recommended' action for a single column filter in Delta Lake. Partitioning creates physical directory structures and can lead to the 'small file problem' if the column has high cardinality. Z-Ordering (or Liquid Clustering in Fabric) is the industry-standard recommendation for improving query performance on specific columns in Delta tables, as it enables data skipping without the overhead of partitioning.
+15 more Ingest and Transform Data questions available
Practice all Ingest and Transform Data questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Ingest and Transform Data. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Ingest and Transform Data questions on the DP-700 frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Ingest and Transform Data is tested as part of the Microsoft Fabric Data Engineer Associate blueprint. Practicing with targeted Ingest and Transform Data questions ensures you can handle any format or difficulty that appears.
Yes. Courseiva provides free DP-700 practice questions across all exam topics and domains. The platform includes topic-based practice, mock exams, missed-question review, bookmarked questions, and readiness tracking — no account required.
Difficulty is subjective, but Ingest and Transform Data is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
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