Microsoft DP-700 Practice Test 40

Question 390

A Dataflow Gen2 refresh fails converting values such as `unknown` to integer. Which correction should be implemented?

Set the Dataflow output column name to Integer without changing its type.
Turn on pipeline activity retries for permanent invalid source tokens.
Identify the failing Power Query type-change step and apply explicit conversion/error handling or quarantine for invalid tokens.
Increase Fabric domain membership for source rows.

Explanation

Correct Answer

Dataflow type conversion follows Power Query semantics; unsupported values must be handled rather than allowed to fail the entire refresh.

Incorrect Answers

A name cannot cast a nonnumeric string into a valid integer value. It does not implement the corrective control requested in this incident.

A deterministic malformed value will fail again until the transformation changes. It does not implement the corrective control requested in this incident.

Governance access cannot repair an invalid Power Query numeric conversion. It does not implement the corrective control requested in this incident.

Question 391

A Dataflow Gen2 preview worked for early rows but the full refresh failed on numeric type conversion. Why can preview and refresh disagree?

The Power Query preview guaranteed that every downstream row contained valid integer text.
The conversion failure means Fabric Delta tables cannot store integers.
A Dataflow can't parse numbers until its item is certified for governance.
The full source contains invalid tokens beyond the previewed subset, so the enforced numeric cast fails during complete evaluation.

Explanation

Correct Answer

A successful sample preview is not proof that every source value conforms to the specified column type.

Incorrect Answers

Preview may sample early valid rows while full refresh encounters later invalid tokens such as `unknown`.

Delta supports integers; the actual issue is conversion of incompatible source text under the defined type.

Endorsement has no role in Power Query type conversion or bad-record handling.

Question 392

A failed Dataflow Gen2 conversion is repaired. What validation is appropriate?

Refresh a dataset containing valid, null and invalid numeric values, then inspect both destination results and documented error/quarantine counts.
Validate only the first ten sample rows that succeeded before the original failure.
Force the conversion error to null without reconciling rejected records or business rules.
Compare only the row count of the destination, ignoring numeric accuracy and rejects.

Explanation

Correct Answer

A mixed-input fixture proves whether the new conversion policy retains valid data and handles malformed values explicitly.

Incorrect Answers

An early-row fixture cannot expose the malformed values encountered in the complete refresh.

Silent coercion can lose significant values and doesn't prove an approved error-handling policy.

The target may have correct counts while quantities are misparsed or silently blanked.

Question 393

An on-premises gateway is required for a Fabric Dataflow Gen2 source, but the dataflow cannot connect. What must be diagnosed?

Rename the dataflow so its title matches the gateway name.
Validate the gateway’s online state, approved connection mapping, source network path and current credentials for the dataflow.
Grant every report reader workspace Admin rights.
Use a OneLake shortcut to the gateway application executable.

Explanation

Correct Answer

The gateway executes access to a network-protected source; a missing or failed gateway route prevents the Power Query connector from reading data.

Incorrect Answers

Matching labels do not map a dataflow to a working gateway data source. It does not implement the corrective control requested in this incident.

Workspace privileges do not fix gateway reachability or external source credentials. It does not implement the corrective control requested in this incident.

A storage shortcut does not proxy the on-premises connector through its runtime host. It does not implement the corrective control requested in this incident.

Question 394

A Dataflow Gen2 refresh fails through a gateway while a browser on an unrelated workstation can reach the source. Select TWO likely causes to investigate.

Browser reachability on an unrelated client proves the on-premises gateway service can authenticate.
The dataflow needs a KQL query acceleration policy before an on-premises gateway is allowed.
An invalid Power BI report label prevents the gateway from serving Dataflow Gen2.
The configured gateway is offline or cannot reach the source from its own network context.
The gateway connection credentials or data source mapping are invalid for this dataflow.

Explanation

Correct Answers

Reachability from a different machine does not prove the gateway host can make the required source connection.

A reachable gateway can still fail if the connector identity or configured source does not authorize the query.

Incorrect Answers

The gateway host, network path, data source binding and credentials are separate from an analyst browser test.

KQL caching is unrelated to the Power Query on-premises connector's gateway requirements.

Reporting labels don't create gateway data source credentials or grant the gateway service network access.

Question 395

The gateway connection is repaired. Which test shows Dataflow Gen2 actually uses the corrected path?

Check only the workstation's connection to the source, without testing through the gateway.
Verify the gateway service is installed but never inspect the configured Dataflow connection.
Run a controlled refresh through the assigned gateway and inspect connector details and representative records delivered to the configured destination.
Run a source query under the owner's identity while ignoring the actual refresh configuration.

Explanation

Correct Answer

An end-to-end gateway-backed query and target-write check validates more than the gateway Online indicator.

Incorrect Answers

The workstation and gateway may have different routing and credentials; the repaired path must be exercised from Fabric.

Service installation alone doesn't establish that the correct source binding and account are selected.

Owner privilege may hide production gateway credential failures and source permission gaps.

Question 396

A Fabric notebook imports a wheel in development but raises ModuleNotFoundError in production. Which runtime configuration should be checked?

Inspect the production notebook’s attached published Fabric environment, library inventory and effective package versions, then publish or attach the required supported wheel.
Change the default lakehouse folder name to match the wheel.
Increase warehouse SQL statistics refresh frequency.
Assign the notebook to a different Fabric domain without updating environment.

Explanation

Correct Answer

Notebook dependencies come from the effective runtime environment; a package installed in a separate development session is not automatically deployed.

Incorrect Answers

Storage naming does not install Python modules into the Spark runtime. It does not implement the corrective control requested in this incident.

A SQL query-planning metric is unrelated to the notebook’s Python import path. It does not implement the corrective control requested in this incident.

Domain classification cannot make an absent package importable. It does not implement the corrective control requested in this incident.

Question 397

A production notebook imports a private module in development but fails in production. The production notebook was explicitly pinned to a different older published Fabric environment, even though the shared workspace default was upgraded with the package. Why does the import still fail?

A wheel uploaded into an unpublished environment becomes visible automatically to all running sessions.
The notebook-level environment binding takes precedence over the workspace default, and the older published environment does not contain the required package version.
The module error is because the lakehouse default mount points to a different folder.
The production workspace requires a Fabric domain with the wheel's package name.

Explanation

Correct Answer

A notebook explicitly attached to an environment does not automatically inherit a changed workspace default. The pinned older published environment must be updated or replaced with the approved package-bearing version.

Incorrect Answers

An unpublished library definition isn't the active configuration, and a running Spark session retains prior dependencies.

Storage mounts don't install a private Python wheel into the notebook's interpreter environment.

Domain governance doesn't publish libraries or control Spark package resolution.

Question 398

After changing the explicitly pinned production notebook to its approved package-bearing environment, what verification proves the original ModuleNotFoundError was resolved under its scheduled identity?

Inspect the environment editor to see the new wheel uploaded but do not start a fresh session.
Test the import only in the development notebook where it originally worked.
Start a new production notebook session with the intended published environment and scheduled execution identity, import the private module, verify its version, and compare expected output.
Compare the notebook names while ignoring the resolved package version.

Explanation

Correct Answer

The actual production session and identity must resolve the intended environment and package; import and output checks verify both dependency availability and downstream function.

Incorrect Answers

Editor presence does not prove that the effective published environment installs the package at runtime.

Development package availability doesn't attest to production environment attachment or installation.

Item names cannot show which wheel build is loaded by the production Spark session.

Question 399

A Fabric notebook reads `Files/raw/2026.csv` using a relative lakehouse path, but its expected default lakehouse is not attached. How should it be corrected?

Create a KQL database with the same display name as the missing lakehouse.
Change the Fabric workspace thumbnail without attaching data.
Disable notebook cell execution error reporting.
Attach the intended lakehouse as the notebook default or use the correct explicit OneLake URI and authorized access path.

Explanation

Correct Answer

Relative Files references rely on the notebook’s lakehouse context; without it, the runtime may not resolve the expected data mount.

Incorrect Answers

A KQL database is a different item and cannot implicitly become a notebook Files mount. It does not implement the corrective control requested in this incident.

UI branding cannot resolve a relative OneLake path. It does not implement the corrective control requested in this incident.

Suppressing exceptions does not create the missing attachment or read permissions. It does not implement the corrective control requested in this incident.

Question 400

A notebook’s default-lakehouse relative path fails after deployment to a new workspace. The notebook was not attached to a lakehouse there. Why?

The relative storage path lacks the lakehouse attachment required to resolve its Files mount in the destination notebook session.
A notebook's relative `Files` path works without a default lakehouse in every workspace.
The referenced CSV is automatically converted to a warehouse SQL table when the notebook runs.
The notebook must create a Fabric domain before reading any file path.

Explanation

Correct Answer

The same text path is not portable unless the destination notebook has an equivalent default lakehouse reference.

Incorrect Answers

The `/lakehouse/default` mount depends on a valid attached/default lakehouse; deployment can leave it absent.

A relative file read needs storage attachment, not SQL table conversion.

Domain association doesn't define the default lakehouse mount used by Spark.

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Question 390

Explanation

Correct Answer

Incorrect Answers

Question 391

Explanation

Correct Answer

Incorrect Answers

Question 392

Explanation

Correct Answer

Incorrect Answers

Question 393

Explanation

Correct Answer

Incorrect Answers

Question 394

Explanation

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Incorrect Answers

Question 395

Explanation

Correct Answer

Incorrect Answers

Question 396

Explanation

Correct Answer

Incorrect Answers

Question 397

Explanation

Correct Answer

Incorrect Answers

Question 398

Explanation

Correct Answer

Incorrect Answers

Question 399

Explanation

Correct Answer

Incorrect Answers

Question 400

Explanation

Correct Answer

Incorrect Answers

Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) Practice Tests