20+ practice questions focused on Implement knowledge mining and information extraction solutions — one of the most tested topics on the Microsoft Azure AI Engineer Associate AI-102 exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Implement knowledge mining and information extraction solutions PracticeYou are designing a knowledge mining solution for a medical research organization. The solution must extract relationships between drugs, diseases, and genes from scientific articles. The data will be stored in a knowledge graph for querying. Which Azure AI service should you use for the extraction?
Explanation: Azure AI Language's healthcare entity recognition and relation extraction is specifically designed to extract medical entities (drugs, diseases, genes) and their relationships from unstructured text, making it ideal for building a knowledge graph. This pre-built model uses deep learning trained on biomedical literature, directly supporting the required extraction without custom training.
Which THREE factors should you consider when designing a knowledge mining solution that uses Azure AI Search and custom skills to extract insights from large volumes of documents?
Explanation: Azure AI Search imposes a timeout on indexer execution, and any custom skill invoked during the enrichment pipeline must complete within that timeout. If the custom skill exceeds the maximum execution time (e.g., 3 minutes for built-in skills or a configurable limit for custom skills), the indexer will fail, causing the entire indexing run to abort. This is a critical design constraint when processing large volumes of documents.
Which TWO configurations are required to enable Azure AI Search to index content from an Azure SQL database?
Explanation: Azure AI Search requires change tracking to be enabled on the Azure SQL table to support incremental indexing. Without change tracking, the indexer would have to re-read the entire table on each run, which is inefficient for large datasets. Change tracking allows the indexer to detect only new, updated, or deleted rows since the last indexing cycle.
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?
Explanation: HTTP 429 errors indicate rate limiting, which occurs when the custom skill sends too many requests to the Azure Machine Learning endpoint in a short period. The skill execution batch size controls how many documents are processed per skill invocation; a large batch size increases call volume and triggers throttling. Reducing the batch size in the skillset definition lowers the request rate, preventing 429 errors.
Your organization uses Microsoft Purview to catalog data assets. You need to enable knowledge mining on these assets to allow users to search across structured and unstructured data. Which integration should you use to connect Microsoft Purview with Azure AI Search?
Explanation: Azure AI Search can use an indexer to connect to Microsoft Purview's Atlas REST API, which allows it to crawl and ingest metadata (e.g., table schemas, file types, classifications) from Purview's data catalog. This integration enables knowledge mining by making both structured and unstructured data assets searchable through a unified Azure AI Search index, without requiring manual metadata push or intermediate tools.
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Practice all Implement knowledge mining and information extraction solutions questions1. Baseline your knowledge
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2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
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4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Implement knowledge mining and information extraction solutions is tested as part of the Microsoft Azure AI Engineer Associate AI-102 blueprint. Practicing with targeted Implement knowledge mining and information extraction solutions questions ensures you can handle any format or difficulty that appears.
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