A notebook in Microsoft Fabric fails with a 'NameError: name 'df' is not defined' error. Which of the following is the most appropriate debugging step?

Change the variable name to something else

Run the entire notebook from the beginning

Check if the cell that defines 'df' was executed before the current cell

An Eventhouse in Microsoft Fabric fails to ingest data because the table schema does not match the incoming data. Which of the following is the most effective way to resolve this?

Delete the table and recreate it

Update the table schema to match the incoming data

Change the data source to one with a matching schema

A OneLake shortcut to an external ADLS Gen2 account is used by a Fabric pipeline that copies data daily. The pipeline fails with 'This request is not authorized to perform this operation.' The shortcut's service principal has Storage Blob Data Reader on the container. The ADLS account's firewall is enabled and allows only selected networks. What is the most likely cause?

The shortcut's path is incorrect

The pipeline's copy activity does not support shortcuts

The service principal's role assignment has not propagated yet

The ADLS account's firewall does not allow the service principal's source IP or the Fabric service's IP

A Fabric notebook that runs a PySpark job fails with 'org.apache.spark.SparkException: Job aborted due to stage failure: Task not serializable'. The notebook defines a custom Python class that is used in a UDF. The class contains a connection object that cannot be serialized. What should you do?

Use a broadcast variable to send the connection object to all executors

Increase the Spark driver memory

Change the notebook's language to Scala

Make the class serializable by removing the connection object and creating it inside the UDF

An Eventhouse query returns incorrect results for a table that is continuously ingested from an Eventstream. The query uses a materialized view. The materialized view's last materialization time is several hours behind the current time. Users need near-real-time results. What should you do?

Change the materialized view's aggregation to a coarser granularity

Run a manual materialization of the view

Disable the materialized view and query the source table directly

Increase the materialized view's lookback period to cover the lag

Microsoft Certified:Fabric Data Engineer Associate

Domain 3Objective 2

Identify and Resolve Errors DP-700 Practice Questions (Page 8)

Part of the Monitor and optimize an analytics solution domain, which accounts for 30–35% of the DP-700 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~12–23 in this domain), expect 4–8 from this objective — we provide 60 practice questions to prepare you well beyond it. (estimate)

60questions here

12free pages

14concepts

30–35%of the exam

Questions 36–40

36foundation · easy
A notebook in Microsoft Fabric fails with a 'NameError: name 'df' is not defined' error. Which of the following is the most appropriate debugging step?
Select an answer first
37foundation · easy
An Eventhouse in Microsoft Fabric fails to ingest data because the table schema does not match the incoming data. Which of the following is the most effective way to resolve this?
Select an answer first
38expert · hard
A OneLake shortcut to an external ADLS Gen2 account is used by a Fabric pipeline that copies data daily. The pipeline fails with 'This request is not authorized to perform this operation.' The shortcut's service principal has Storage Blob Data Reader on the container. The ADLS account's firewall is enabled and allows only selected networks. What is the most likely cause?
Select an answer first
39application · medium
A Fabric notebook that runs a PySpark job fails with 'org.apache.spark.SparkException: Job aborted due to stage failure: Task not serializable'. The notebook defines a custom Python class that is used in a UDF. The class contains a connection object that cannot be serialized. What should you do?
Select an answer first
40expert · hard
An Eventhouse query returns incorrect results for a table that is continuously ingested from an Eventstream. The query uses a materialized view. The materialized view's last materialization time is several hours behind the current time. Users need near-real-time results. What should you do?
Select an answer first

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