DP-700 Ingest and Transform Data Practice Question
Your organization wants to implement near real-time data ingestion from an Azure SQL Database into Fabric for reporting. You must minimize the impact on the source database's performance and avoid manual pipeline scheduling. Which solution should you implement?
⚠ Common exam trap
Candidates often suggest standard Data Factory pipelines because they are familiar, overlooking the 'Mirroring' feature specifically designed for low-latency, non-intrusive synchronization from Azure SQL databases.
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
✓
Fabric Mirroring for Azure SQL Database.
Mirroring in Fabric provides a low-latency, continuous synchronization path from supported databases. It uses the source database's transaction log to capture changes (CDC), which is much more efficient than traditional polling and does not require the user to manage complex schedules or orchestration pipelines to keep data synchronized.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A Pipeline with a Copy Activity using a 'Tumbling Window' trigger.
Why it's wrong here
Tumbling Window triggers allow for scheduled data movement but still rely on periodic polling of the source database. This approach creates recurring load on the source and is not truly near real-time, as it introduces latency based on the interval of the window defined in the pipeline.
- ✗
A Dataflow Gen2 with incremental refresh enabled.
Why it's wrong here
While Dataflow Gen2 supports incremental refresh, it still requires a scheduled refresh interval and executes Power Query logic to identify changes. This process is generally more resource-intensive on both the source and Fabric compared to the log-based change data capture used by the Mirroring feature.
- ✓
Fabric Mirroring for Azure SQL Database.
Why this is correct
Mirroring automatically replicates data from Azure SQL Database to Fabric OneLake in near real-time. It leverages the underlying transaction logs to sync changes, ensuring minimal performance impact on the source system while providing an always-up-to-date replica for analytical workloads without manual scheduling.
- ✗
A Spark Notebook using the 'JDBC' connector in a loop.
Why it's wrong here
Using a Spark Notebook in a continuous loop to query a source database is highly inefficient and difficult to manage. It places a significant and constant load on the source database's compute resources and requires custom error-handling logic to ensure data consistency and reliability.
About these practice questions
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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-700 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-700 exam.