AI-900 Question 27
Single answerA company wants to analyze a large repository of unstructured documents, including PDFs and scanned images, to extract insights and identify key information such as customer names, dates, and transaction details. Which Azure AI service workload is most appropriate for this scenario?
- A
Knowledge mining
- B
Computer vision
- C
Natural language processing
- D
Machine learning model training
Show answer and explanation
Correct answer: A
Explanation
The scenario describes analyzing unstructured documents to extract key insights, which is a typical knowledge mining workload. Azure Cognitive Search, a core component of knowledge mining, enables businesses to extract information from diverse document formats and structure it for search and analysis. This makes knowledge mining the most appropriate choice for this use case.
- A. Correct.
Knowledge mining is the most suitable workload for extracting insights from unstructured data, such as documents, by leveraging tools like Azure Cognitive Search to index, extract, and analyze information.
- B. Incorrect.
Computer vision focuses on analyzing visual content, such as recognizing objects or faces in images, but it is not designed for processing and extracting insights from large repositories of unstructured documents.
- C. Incorrect.
Natural language processing is used to understand and process human language, but it does not include the comprehensive indexing and search capabilities required for knowledge mining scenarios.
- D. Incorrect.
Machine learning model training involves creating and training custom models for specific tasks, but it is not directly applicable to the knowledge mining use case described in the scenario.