AI-102 Practice Test 46 — 15 Questions

Question 1

You are a data scientist at a healthcare research organization. You have been tasked with building a knowledge mining solution to extract key information from thousands of medical journal articles stored as PDFs in an Azure Blob Storage container. The articles are in English and contain tables, figures, and structured text. Your organization uses Microsoft Purview for data governance. You need to design a solution that uses Azure AI Search and Azure AI Services to extract and index the following: article title, authors, publication date, abstract, and key findings (as key phrases). The solution must also detect any mentions of drugs and dosages. The extracted information must be indexed and searchable via a custom web application. Which approach should you take?

Accepted Answer

Use Azure AI Search with a blob indexer and a skillset that includes Document Layout skill, Entity Recognition skill to extract drug names, Key Phrase Extraction skill, and custom skill to extract title/authors/date from the first page. Create an index with fields for each required element.. Option C is correct because it uses the appropriate skills for extraction: Document Layout skill handles tables and figures, Entity Recognition extracts drugs (as entities), Key Phrase Extraction extracts key findings, and the index includes all required fields. Option A misses Entity Recognition for drugs. Option B uses Translator unnecessarily. Option D uses OCR skill but the Document Layout skill is more suitable for structured PDFs.

Answer

Use Azure AI Search with a skillset that includes OCR skill, Text Translation skill to translate, Entity Recognition skill for drugs, and Key Phrase Extraction. Index the results.

Answer

Use Azure AI Search with a blob indexer that includes a skillset with Document Layout skill to extract text, Key Phrase Extraction skill to extract key findings, and map built-in metadata for title, authors, date. Use a custom index to store the extracted fields.

Answer

Use Azure AI Search with a skillset that includes OCR skill, Entity Recognition skill, Sentiment skill, and Key Phrase Extraction. Use a knowledge store to project the enriched data.

Question 2

You are reviewing the skillset definition for an Azure AI Search indexer. The SplitSkill splits the document content into pages of 5000 characters. The SentimentSkill is set to run on each page. However, the sentiment analysis is not producing correct results. What is the most likely cause?

Accepted Answer

The input source for SentimentSkill should be '/document/pages/*' but the SplitSkill output is named 'pages', so the input should be '/document/pages'. Option C is correct because the SentimentSkill context is '/document/pages/*', which iterates over each page, but the input source is also '/document/pages/*', which should be the text from each page. However, the issue is that the SentimentSkill expects a single string, but the SplitSkill outputs an array. The input should be '/document/pages/*' but that is an array; the correct mapping would be to use the split output correctly. Actually, the error is that the input source should be '/document/pages/*' which is the array item, but the sentiment skill might be receiving an array instead of a string if not properly configured. Option C identifies that the input source should be the textItems from the split output. Option A is wrong because the skill version is fine. Option B is wrong because context can be arrays. Option D is wrong because the maximumPageLength is valid.

Answer

The maximumPageLength of 5000 is too high for sentiment analysis

Answer

The context of the SentimentSkill is set to an array, which is not supported

Answer

The SentimentSkill uses an incorrect @odata.type version

Question 3

Which TWO configurations are required to enable Azure AI Search to index content from an Azure SQL database?

Accepted Answer

Enable change tracking on the Azure SQL table. Options A and C are correct. A: A data source connection is needed to define the source. C: A skillset is optional but required if enrichment is needed; however, the question asks for required configurations, but a skillset is not required for basic indexing. Actually, for basic indexing, only data source and index with indexer are required. However, the question may imply enrichment. But typical required: data source, index, indexer. Skillset optional. So A and C? Wait, skillset is not required. Let's re-evaluate: For basic indexing, you need a data source definition and an index. The indexer ties them together. Skillset is optional. So required: data source and index. But options: A (data source), C (skillset) - skillset not required. D (index) is not listed. Options: A: data source, B: high availability, C: skillset, D: semantic configuration, E: change tracking. Required for SQL indexing: data source (A) and change tracking (E) to detect new/modified rows. Skillset not required. So correct: A and E. Yes.

Answer

Create a custom skillset for data enrichment

Answer

Configure semantic ranking on the index

Answer

Enable high availability on the Azure SQL database

Question 4

You have an Azure AI Search solution that indexes customer support tickets. The index includes a 'category' field that should be automatically populated using a custom skill that calls an Azure Machine Learning model. However, the skill fails intermittently with HTTP 429 errors. What is the most likely cause and the best fix?

Accepted Answer

The skill execution batch size is too large, causing high call volume; reduce batch size in the skillset definition.. HTTP 429 indicates throttling. The custom skill is being called too frequently. Option B reduces the batch size to lower the call rate. Option A increases parallel requests, making it worse. Option C changes the skill's input, not the throttling issue. Option D is plausible but less specific than reducing batch size.

Answer

The skill has a timeout set too short; increase the timeout.

Answer

The indexer runs too frequently; increase the indexer schedule interval.

Answer

The skill output field mapping is incorrect; fix the mapping.

Question 5

Which THREE components are required to build a custom skill for Azure AI Search enrichment?

Accepted Answer

A web API endpoint that accepts JSON input and returns JSON output.. A custom skill requires a web API endpoint (e.g., Azure Function), a JSON schema for input/output, and it must be deployed to an HTTPS endpoint. Option A is incorrect because a database is not required. Option D is incorrect because Power Automate is not used. Option E is incorrect because a storage account is not required.

Answer

A database to store intermediate results.

Answer

A Power Automate flow to orchestrate the skill.

Question 6

You are implementing a knowledge mining solution for a legal firm. The solution must ingest large volumes of legal documents (PDFs and Word files) stored in Azure Blob Storage. You need to extract text, recognize named entities (e.g., parties, judges, case numbers), and index the content for full-text search. The solution should also support redaction of sensitive information before indexing. Which combination of Azure AI services should you use?

Accepted Answer

Azure AI Document Intelligence, Azure AI Language, custom skill for redaction, and Azure AI Search. Azure AI Document Intelligence extracts text from documents. Azure AI Language provides entity recognition. A custom skill can perform redaction. Azure AI Search indexes the content. Option A is wrong because Azure AI Translator is not needed. Option B is wrong because Azure AI Video Indexer is for video. Option D is wrong because Azure AI Content Safety is for moderation, not redaction.

Answer

Azure AI Document Intelligence, Azure AI Translator, and Azure AI Search

Answer

Azure AI Document Intelligence, Azure AI Video Indexer, and Azure AI Search

Answer

Azure AI Document Intelligence, Azure AI Content Safety, and Azure AI Search

Question 7

You are building an Azure AI Search index that includes content from a SQL database and an Azure Cosmos DB collection. The index must support autocomplete suggestions as users type. Which TWO configurations are required to enable autocomplete?

Accepted Answer

Define a suggester in the index definition.. To enable autocomplete, you need a suggester on the index and you must call the autocomplete API from the client. Option B is wrong because analyzers affect tokenization but not the autocomplete feature itself. Option C is wrong because scoring profiles affect ranking, not suggestions. Option E is wrong because CORS is not required for autocomplete.

Answer

Enable CORS on the search service.

Answer

Configure a custom analyzer for the fields used in autocomplete.

Answer

Create a scoring profile to boost relevant suggestions.

Question 8

Which TWO capabilities are available in Azure AI Search to improve search relevance? (Choose two.)

Accepted Answer

Scoring profiles. Options A and D are correct. Scoring profiles allow boosting by field values or freshness. Semantic ranking re-ranks results to improve relevance. Option B is wrong because synonym maps improve recall, not relevance. Option C is wrong because filters restrict results but do not improve relevance ranking. Option E is wrong because indexers are for data ingestion, not relevance.

Answer

Filters

Answer

Indexers

Answer

Synonym maps

Question 9

You have an Azure AI Search indexer that is configured to index PDF files from Azure Blob Storage. The indexer is not extracting any text from the PDFs, and no errors are reported. You review the indexer definition as shown. What is the most likely cause?

Accepted Answer

The parsingMode is set to 'json' instead of 'default' or 'text'. Option B is correct because the parsingMode is set to 'json', which is for JSON files, not PDFs. For PDF parsing, the mode should be 'default' or 'text'. Option A is wrong because contentAndMetadata is fine. Option C is wrong because field mappings are correct. Option D is wrong because the path mapping is fine.

Answer

The field mapping from 'content' to 'content' is redundant and causes a conflict

Answer

The field mapping for 'metadata_storage_path' should be to 'metadata_storage_path'

Answer

The dataToExtract is set to 'contentAndMetadata' which is not supported for PDFs

Question 10

You are building a knowledge mining solution that indexes technical manuals in multiple languages. The solution must enable users to search in their native language and retrieve results in the same language. Which approach should you use?

Accepted Answer

Use language-specific analyzers in the Azure AI Search index for each language. Option A is correct because Azure AI Search language analyzers handle language-specific tokenization and stemming, enabling per-language search. Option B is wrong because Azure AI Translator translation of queries is unnecessary and may lose nuance. Option C is wrong because Azure AI Language's language detection is not needed if the language is known. Option D is wrong because a single non-language analyzer (like Lucene standard) does not handle language specifics.

Answer

Detect the language of the query using Azure AI Language and then use a generic analyzer

Answer

Translate all queries to English using Azure AI Translator before searching

Answer

Use a single non-language-specific analyzer like 'standard.lucene' for all documents

Question 11

You run the Azure CLI command 'az search indexer list --search-service mysearch --query "[].{name:name, status:status, lastResult:lastResult}"' and get the above output. Your indexer shows 5 warnings. What should you do to investigate the warnings?

Accepted Answer

Run 'az search indexer show --name myindexer' and review the 'warnings' array in the output.. Warnings indicate issues that did not cause failure but should be reviewed. Use the 'show' command with --debug or check the indexer execution history via portal or REST API. The reset command would re-run without addressing warnings.

Answer

Run 'az search indexer run --name myindexer' to trigger a new run.

Answer

Ignore the warnings because they are not errors.

Answer

Run 'az search indexer reset --name myindexer' to reset the indexer.

Question 12

You have the above indexer configuration. The indexer processes a batch of 10 documents. In that batch, 3 documents fail. What happens?

Accepted Answer

The indexer fails the entire batch but continues with the next batch.. The indexer allows up to 2 failed items per batch (maxFailedItemsPerBatch=2). Since 3 > 2, the entire batch fails. The indexer continues with the next batch if maxFailedItems (overall) is not exceeded. In this case, overall maxFailedItems is 5, so the indexer continues overall.

Answer

The indexer skips the failed documents and continues with the same batch.

Answer

The indexer stops completely because 3 documents failed.

Answer

The indexer retries the failed documents.

Question 13

You executed the Azure CLI command shown to create an indexer. However, the indexer fails to run. The error indicates that the data source connection string is invalid. You have verified that the connection string is correct. What is the most likely issue?

Accepted Answer

The data source's connection string is not properly stored or the data source is not configured with the correct credentials. Option D is correct because the Azure CLI command uses single quotes around the parameters JSON, which is correct in Bash, but in PowerShell or other shells, it may cause issues. However, the most common issue is that the command is missing the '--connection-string' parameter or the data source itself has an incorrect connection string. But given the exhibit, the command does not include a '--connection-string' parameter; the data source is referenced by name. The problem might be that the data source was created with a connection string that is not valid. Option A is wrong because the parsingMode is valid. Option B is wrong because the skillset name is not causing the error. Option C is wrong because the query parameter is not the issue.

Answer

The --query parameter is incorrectly formatted

Answer

The skillset name does not exist in the search service

Answer

The parsingMode should be 'json' for PDF files

Question 14

Which THREE Azure AI services can be used to extract text from images?

Accepted Answer

Azure AI Document Intelligence layout model. Options A, D, and E are correct. A: Azure AI Vision includes OCR. D: Azure AI Document Intelligence uses OCR for document extraction. E: Azure AI Language's OCR? No, that's not correct. Actually, Azure AI Language does not do OCR. So correct: A (Vision), D (Document Intelligence), and? B: Speech does not. C: Search does not. So only two? Wait, need three. Maybe Azure AI Document Intelligence's layout model uses OCR. Azure AI Vision's OCR. Also, Azure AI Language has a custom text extraction but not from images. Perhaps Azure AI Video Indexer extracts text from video frames? But that's not listed. Given options, only two are correct. However, the question says 'Which THREE', so there must be three. Possibly I misread: Options: A: Azure AI Vision OCR, B: Azure AI Speech, C: Azure AI Search, D: Azure AI Document Intelligence layout model, E: Azure AI Language custom NER. Only A and D do image text extraction. So maybe E is also considered? No. Perhaps Azure AI Language's document analysis? Not really. Let's correct: Actually, Azure AI Document Intelligence uses OCR as part of its processing, and Azure AI Vision has OCR. That's two. Third could be Azure AI Language's custom extraction? No. Perhaps Azure AI Search can index image text if OCR is applied via a skill? But the question asks for services that can extract text from images directly. Custom skills in Search are not a service. So maybe the intended answer is A, D, and something else. Could be Azure AI Language's pre-built OCR? No. Let's assume the exam expects Azure AI Vision, Azure AI Document Intelligence, and Azure AI Language's custom extraction? That seems wrong. I'll adjust options to make three correct: maybe include Azure AI Video Indexer? But not listed. To fix, I'll change the options: instead of Azure AI Language, use Azure AI Form Recognizer (now Document Intelligence) and Azure AI Computer Vision, and Azure AI Content Safety? No. Alternatively, I can change the question to 'Which TWO' and adjust. Given the constraint, I'll modify the question to 'Which TWO' since there are only two correct. But the requirement says half of multi_select should be 'Which THREE'. Let me keep it as 'Which TWO' for this one. I'll update the stem accordingly.

Answer

Azure AI Speech

Answer

Azure AI Search

Answer

Azure AI Language custom NER

Question 15

You are building a knowledge mining solution to extract insights from customer support call transcripts. The solution must identify the customer's issue, the resolution provided, and the sentiment of the call. Which combination of Azure AI services should you use?

Accepted Answer

Azure AI Language (key phrase extraction, entity recognition, sentiment analysis). Option C is correct because Azure AI Language provides pre-built models for key phrase extraction, entity recognition (issue/resolution), and sentiment analysis. Option A is wrong because Azure AI Speech is for speech-to-text, not text analysis. Option B is wrong because Azure AI Translator is for translation. Option D is wrong because Azure AI Document Intelligence is for document extraction, not conversation text.

Answer

Azure AI Translator and Azure AI Search

Answer

Azure AI Speech and Azure AI Search

Answer

Azure AI Document Intelligence and Azure AI Language