Objective 3.2
DP-700Identify and resolve errors
Objective 3.2 sits in Monitor and optimize an analytics solution, which carries 34% of the DP-700 Fabric Data Engineer exam. The questions below are original, written from the official objective title above, and each explanation cites the Microsoft Azure page it rests on.
Objective title verbatim from the official objectives. Microsoft Azure exam page ↗
A worked example
Shown solved, with the whole explanation open: this is what every question here carries.
A warehouse query is slow on its first run but fast afterward. Which column confirms a cold start pulled data from remote storage?
Correct.
Checked against learn.microsoft.com, August 2026Concept
A first execution has nothing in memory, so the engine pulls the bytes it needs across the network from OneLake; later executions do not. Query insights records how many megabytes came from that distant source, and a nonzero figure is the tell.
Why D
A nonzero data_scanned_remote_storage_mb value indicates a cold start.
Source
Microsoft Learn, Warehouse Performance Guidelines, checked August 2026A nonzero value in data_scanned_remote_storage_mb indicates a cold start. The query execution fetched data from OneLake.
Now you: objective 3.2 questions
No account needed. The explanation opens when you answer.
Sample question 1 of 3
To inspect current locks and conflicts in a warehouse, which view do you query?
Sample question 2 of 3
A pipeline app hits transient write-write conflicts with warehouse background compaction. What is recommended?
Sample question 3 of 3
Which query insights view lists the most frequently run warehouse queries?
That’s 3 of the full DP-700 Fabric Data Engineer bank.
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Continue practicingRead the sources
These are the official pages the questions above cite. Reading them is studying the objective from the primary source, which is what the explanations point you toward anyway.