Microsoft Updated AI-102 Exam Questions and Answers by ioan

A data warehouse is designed for analytical workloads (OLAP) , not transactional workloads (OLTP).

It integrates data from multiple sources and supports complex queries, aggregations, and reporting for decision-making.

A. storage for transactional LOB apps → describes OLTP (e.g., SQL Server, Azure SQL Database), not a data warehouse.

B. transformation services → describes ETL/ELT pipelines (e.g., Data Factory), not the warehouse itself.

C. read-only storage of historical data → partially true but too narrow; the key feature is analytics, not just storage.

D. answers to complex queries across multiple sources → Correct and complete definition.

Correct Answer: D

The scenario involves a Language Understanding (LUIS) or Conversational Language Understanding (CLU) model that has:

An intent called FindContact (used for searching a contact list).

Training phrases like:

“Find contacts in London”

“Who do I know in Seattle?”

“Search for contacts in Ukraine”

Key Requirement

The model must recognize locations (London, Seattle, Ukraine) inside the FindContact intent.

Why the Solution is Incorrect

The proposed solution is to create a new intent for location.

This is not correct because:

Intents represent what the user wants to do (the action, e.g., FindContact ).

Entities represent details within the user’s utterance (the data, e.g., location ).

Here, the intent is already defined: FindContact .

Location should be modeled as an entity (Location entity), not as a separate intent.

Creating a new intent for each location (London, Seattle, Ukraine) would fragment the model and make it harder to generalize. Instead, the model should capture location as a parameter of the single intent FindContact .

Correct Approach

Keep the existing FindContact intent.

Add an entity for location (prebuilt GeographyV2 in LUIS or “Location” entity in CLU).

Train the model so that London , Seattle , Ukraine are recognized as entity values inside the FindContact intent.

Correct Answer: B. No

Microsoft References

Intents and entities in Language Understanding

Prebuilt entity: GeographyV2

Comprehensive Detailed Explanation

The method shown uses the Read API of the Azure Computer Vision client library. The ReadAsync call submits the OCR job and returns an Operation-Location header, which contains the operationId. Then GetReadResultAsync(Guid.Parse(operationId)) is called to fetch the result.

The Issue

The Read API is asynchronous.

Submitting the read request does not mean the OCR has finished.

If you immediately call GetReadResultAsync , the operation may still be in progress, resulting in incomplete or empty results.

Required Fixes

Check the results.Status property

The response from GetReadResultAsync includes a status property.

Possible values: notStarted , running , succeeded , failed .

You must wait until the status is succeeded before processing results.

This ensures you don’t attempt to read lines before OCR has completed.

This corresponds to B.

Wrap in a loop with delay

Since OCR takes time, you need to poll the service until the status becomes succeeded or failed .

A typical pattern is:

ReadOperationResult results;

do

{

results = await client.GetReadResultAsync(Guid.Parse(operationId));

await Task.Delay( 1000 ); // wait 1 second before retrying

}

while (results.Status == OperationStatusCodes.Running || results.Status == OperationStatusCodes.NotStarted);

This corresponds to D.

Option Analysis

A. Remove the Guid.Parse(operationId) parameter

Incorrect. The operationId is required to fetch the OCR results.

B. Add code to verify the results.Status value

Correct. You must check whether the operation has completed.

C. Add code to verify the status of the txtHeaders.Status value

Incorrect. txtHeaders only contains metadata and the operation location. The OCR completion status comes from the results.Status in the GetReadResultAsync response, not from txtHeaders .

D. Wrap the call to GetReadResultAsync within a loop that contains a delay

Correct. This is how you poll until the operation has finished.

Correct Answer: B and D

Microsoft References

Azure Computer Vision Read API

Read text using the Computer Vision client library