AI-102 Practice Test 48 — 15 Questions

Question 1

You are building a knowledge mining solution using Azure AI Search and Azure AI Language. The solution must extract key phrases, entities, and sentiment from customer feedback documents. After processing, the enriched content should be stored in the search index for full-text search. You need to configure the enrichment pipeline. Which two Azure AI services should you integrate?

Accepted Answer

Azure AI Language and Azure AI Search. Azure AI Language provides key phrase extraction, entity recognition, and sentiment analysis as built-in skills. Azure AI Search provides the indexing and search capabilities. Option A is wrong because Azure AI Translator is for translation, not the required analyses. Option B is wrong because Azure AI Document Intelligence is for extracting text from documents, not for language analysis. Option D is wrong because the custom skill would be redundant if native skills exist.

Answer

Azure AI Language and a custom skill in Azure Functions

Answer

Azure AI Translator and Azure AI Search

Answer

Azure AI Document Intelligence and Azure AI Search

Question 2

You are building a chatbot using Microsoft Copilot Studio that needs to answer questions based on content from a set of technical manuals stored as PDFs. The content must be indexed and made available to the chatbot. You need to configure the knowledge source for the chatbot. What should you do?

Accepted Answer

Create an Azure AI Search index from the PDFs and connect it to Copilot Studio as a knowledge source.. Microsoft Copilot Studio can use Azure AI Search as a knowledge source to index and retrieve content from PDFs. Option A is wrong because the Web search is for public information. Option B is wrong because SharePoint is not the direct indexer for PDFs. Option D is wrong because Azure SQL Database is not for document content.

Answer

Upload the PDFs to a SharePoint library and use SharePoint as the knowledge source.

Answer

Add a web search connector to the chatbot to search for information online.

Answer

Store the content in Azure SQL Database and use it as a knowledge source.

Question 3

You have an Azure AI Search skillset defined as shown in the exhibit. When you run the indexer, the enrichment pipeline produces outputs but no entities are extracted. The source documents are in English and contain clear organization and person names. What is the most likely cause?

Accepted Answer

The '/document/content' field is an array, but the skill expects a string.. The default version of EntityRecognitionSkill (V3) requires the 'text' input to be a string, not an array. If '/document/content' is an array (e.g., from OCR output), the skill fails silently. Option A is wrong because the language is correct. Option B is wrong because the skill outputs are configured. Option D is wrong because the skill is in the correct order (no dependency).

Answer

The skill output is not mapped to the index.

Answer

The skills are in the wrong order.

Answer

The documents are not in English.

Question 4

Your organization uses Azure AI Search to index customer product reviews. The reviews are in English, Spanish, and French. You need to enable multi-lingual search so that a query in English returns relevant results from all three languages. What should you do?

Accepted Answer

Create separate search fields for each language, each with the corresponding language analyzer (e.g., 'en.microsoft', 'es.microsoft', 'fr.microsoft').. Azure AI Search supports multi-lingual search by assigning language-specific analyzers per field. For cross-lingual search, you can use a single field with a language-agnostic analyzer like 'standard' or use multiple fields and query them. The best practice is to use separate fields per language with appropriate analyzers and search across all of them.

Answer

Use Azure AI Translator to translate all reviews to English before indexing.

Answer

Use a single field with the 'standard' analyzer for all languages.

Answer

Use the 'keyword' analyzer for all fields.

Question 5

You are building a knowledge mining solution that uses Azure Cognitive Search and Azure AI Language. The solution must extract key phrases and detect the language of documents. Which THREE components are required?

Accepted Answer

A search index that contains fields for the extracted data.. Options A, C, and D are correct. A skillset with key phrase extraction and language detection skills (A), a data source connecting to the documents (C), and a search index to store the enriched data (D). Option B is wrong because the indexer is required, but the index is needed too. Option E is wrong because custom skills are not required.

Answer

A custom skill to combine key phrases and language.

Answer

An indexer that runs on a schedule.

Question 6

You deploy the ARM template shown in the exhibit to create an Azure AI Search indexer. The indexer fails to run, and you see an error that the skillset 'demo-skillset' does not exist. What is the most likely cause?

Accepted Answer

The skillset resource was not deployed before the indexer. Option A is correct because the ARM template references a skillset that has not been deployed. Option B is wrong because the data source is referenced but not necessarily missing. Option C is wrong because the schedule is valid. Option D is wrong because the field mapping is valid.

Answer

The field mapping source field 'metadata_storage_path' is incorrect

Answer

The schedule start time is in the past, causing the indexer to be disabled

Answer

The data source 'demo-datasource' does not exist

Question 7

You are using Azure AI Search to build a knowledge base for a customer support portal. The index includes a 'sentiment' field that should be populated using the Sentiment skill. However, the sentiment scores are not being written to the index. The skillset runs successfully. What is the most likely cause?

Accepted Answer

The output field mapping for 'sentiment' is missing or incorrectly defined in the indexer.. Option C is correct: the output field mapping in the indexer is missing or incorrect. Option A is incorrect because the skill ran successfully. Option B is incorrect because the sentiment skill does not require a specific data type. Option D is incorrect because indexer execution is successful.

Answer

The Sentiment skill is not correctly configured in the skillset.

Answer

The indexer is in a failed state and not processing documents.

Answer

The sentiment field in the index is of type 'Collection(Edm.String)' but the skill outputs a double.

Question 8

You are designing an Azure AI Search solution that indexes customer support tickets from a SQL database and also from a custom CRM system via a custom API. The index must support scoring profiles that boost tickets from VIP customers. The VIP status is stored in the CRM system. You need to ensure that the boost factor is applied correctly. What should you do?

Accepted Answer

Include the VIP status field in the index by pushing it from the CRM system via the push API, then use a scoring profile with a field boost.. A scoring profile can use a field (e.g., isVIP) to boost results. The field must be present in the index. You can push the VIP data to the index via the push API alongside the CRM data. Option A is wrong because a custom analyzer does not handle boosting. Option B is wrong because the scoring profile cannot dynamically fetch data from an external source during query time. Option D is wrong because the scoring profile uses fields already in the index.

Answer

Use a scoring profile with a tag boost that references a field in the SQL database.

Answer

Use a scoring profile with a function that queries the CRM system at query time.

Answer

Configure a custom analyzer that boosts VIP terms.

Question 9

You are extracting text from scanned documents that are in French. Which capability of Azure AI Document Intelligence should you use?

Accepted Answer

Read API. Option C is correct because the Read API supports multiple languages including French for OCR. Option A is wrong because the Layout model extracts tables but not necessarily text in specific languages. Option B is wrong because the custom model requires training. Option D is wrong because the prebuilt invoice model is for invoices and may not support all languages or general text extraction.

Answer

Custom model

Answer

Layout model

Answer

Prebuilt invoice model

Question 10

Refer to the exhibit. You have this Azure AI Search indexer configuration. The indexer is failing after processing 6 documents that contain errors. What should you do to ensure the indexer continues processing even if some documents fail?

Accepted Answer

Increase maxFailedItems to a higher value, such as 100. Option B is correct. The current configuration has maxFailedItems=5, meaning the indexer stops after 5 failures. Increasing maxFailedItems to a higher value (e.g., 100) allows the indexer to continue. Option A is wrong because decreasing batch size may reduce failures but does not increase the failure tolerance. Option C is wrong because removing the schedule does not affect failure handling. Option D is wrong because increasing batch size may increase failures.

Answer

Decrease the batch size to 5

Answer

Increase batch size to 20

Answer

Remove the schedule to run the indexer on demand

Question 11

You are developing a knowledge mining solution that extracts insights from customer feedback. Which TWO Azure AI services can be used to analyze the sentiment of the feedback and categorize it into topics?

Accepted Answer

Azure AI Language. Option A (Azure AI Language) provides sentiment analysis and topic extraction. Option D (Azure AI Search with cognitive skills) can incorporate sentiment and topic extraction skills. Option B is for decision, not sentiment. Option C is for text translation. Option E is for computer vision.

Answer

Azure AI Personalizer

Answer

Azure AI Translator

Answer

Azure AI Custom Vision

Question 12

You are building a knowledge mining solution for legal documents using Azure AI Search. The solution must extract entities like dates, organizations, and persons from PDF files and index them. Which built-in skill should you add to the skillset to perform this extraction?

Accepted Answer

Named Entity Recognition skill. The Named Entity Recognition (NER) skill extracts entities like persons, organizations, and dates from text. Option A is incorrect because OCR is for extracting text from images, not entities. Option C is incorrect because Key Phrase Extraction extracts key phrases, not named entities. Option D is incorrect because Language Detection identifies language.

Answer

Language Detection skill

Answer

Optical Character Recognition (OCR) skill

Answer

Key Phrase Extraction skill

Question 13

Which TWO Azure AI services can be used together to build a knowledge mining solution that extracts text from handwritten notes and indexes them for search?

Accepted Answer

Azure AI Search. Azure AI Vision Read API can extract text from handwritten notes (OCR). Azure AI Search indexes the extracted text. Option A is incorrect because Document Intelligence is for forms, not handwriting. Option C is incorrect because Language is for text analysis. Option D is incorrect because Translator is for translation.

Answer

Azure AI Document Intelligence

Answer

Azure AI Language

Answer

Azure AI Translator

Question 14

You have configured an Azure AI Search indexer with a Cosmos DB data source as shown in the exhibit. The indexer runs successfully, but you notice that the index is missing some documents that were recently added to Cosmos DB. What is the most likely cause?

Accepted Answer

The high water mark is not being updated correctly, causing some documents to be skipped.. The query uses '@HighWaterMark' which is a placeholder for the high water mark value used for change tracking. However, the query includes 'WHERE c._ts > @HighWaterMark' which filters out documents with a timestamp less than or equal to the high water mark. If the high water mark is not being updated correctly or if documents have the same timestamp, they might be missed. Option A is wrong because the change tracking is enabled by the query using _ts. Option B is wrong because the query selects all fields needed. Option C is wrong because the container name is correct. Option D is wrong because the connection string is valid since the indexer runs successfully.

Answer

The indexer is not configured to track changes using _ts.

Answer

The container name is misspelled.

Answer

The query does not select all fields required by the index.

Question 15

Your company has a large repository of scanned invoices in PDF format. You need to extract invoice number, date, total amount, and vendor name from these PDFs. Which Azure AI service should you use?

Accepted Answer

Azure AI Document Intelligence. Azure AI Document Intelligence (formerly Form Recognizer) is designed for extracting structured data from forms and documents. Pre-built invoice model can extract invoice fields. Azure AI Language is for text analytics on extracted text.

Answer

Azure AI Language

Answer

Azure AI Search

Answer

Azure AI Vision