ai-102_module_12

our organization aims to build a knowledge mining solution to extract insights from a large volume of unstructured data, such as documents and images. What Azure service should you use for this purpose?

• a. Azure Machine Learning

• b. Azure Cognitive Services

• c. Azure Cognitive Search

• d. Azure Data Lake Storage

You are developing a solution that involves searching and retrieving information from a vast collection of documents, enabling users to find relevant content quickly. Which Azure service provides powerful search capabilities for this task?

• a. Azure Logic Apps

• b. Azure Databricks

• c. Azure Cognitive Search

• d. Azure Data Factory

Your knowledge mining solution needs to index data from various sources, including SQL databases, Azure Blob Storage, and external websites. What components should you configure to connect to these data sources?

• a. Skillsets and indexers

• b. Skillsets and custom skills

• c. Data sources and skillsets

• d. Indexers and custom skills

You want to define the structure of data extracted during the indexing process, including which fields to extract, their data types, and how they are named. What Azure component is used for this purpose?

• a. Data sources

• b. Skillsets

• c. Indexers

• d. Indexes

You are configuring an indexer in Azure Cognitive Search to extract data from Azure SQL Database. What role does the indexer play in the indexing process?

• a. It connects to data sources.

• b. It defines the schema of the index.

• c. It extracts, transforms, and indexes data.

• d. It manages security and authentication.

Your knowledge mining solution requires custom data processing, such as entity recognition or sentiment analysis, during indexing. What Azure feature allows you to integrate custom code for these tasks?

• a. Skillsets

• b. Data sources

• c. Indexers

• d. Custom skills

You want to store extracted knowledge and insights for long-term analysis and reporting. What Azure component serves as the storage repository for structured data created during the indexing process?

• a. Skillsets

• b. Data sources

• c. Indexers

• d. Knowledge store

During the indexing process in Azure Cognitive Search, what is the purpose of an indexer?

• a. To define the schema of the index

• b. To extract and transform data from data sources

• c. To query and retrieve data from an index

• d. To manage security and access control

What is the primary benefit of using Azure Cognitive Search for knowledge mining and information retrieval?

• a. Real-time data processing

• b. Scalable and efficient search capabilities

• c. Advanced machine learning models

• d. Streamlined data storage

Your organization needs to update the search index with new content on a daily basis. Which Azure component is responsible for periodically refreshing and updating the index?

• a. Skillsets

• b. Data sources

• c. Indexers

• d. Indexes