Microsoft Azure Data FundamentalsDescribe core data conceptsHard
A data architect is designing a system to store invoices, which are primarily PDF documents, along with associated metadata such as customer name, invoice date, and total amount. The system needs to allow users to search for invoices based on this metadata and potentially the content within the PDF files themselves. Which type of database or storage is MOST suitable for this requirement?
- AAzure Data Lake Storage Gen2
- BAzure Cosmos DB (MongoDB API)
- CAzure SQL Database
- DAzure Cognitive Search
Show answer & explanationAnswer & explanation
Correct answer: D. Azure Cognitive Search
While other options can store the files, Azure Cognitive Search is specifically designed for full-text search over various content types, including PDFs, and provides rich querying capabilities on both content and metadata, making it ideal for invoice search.
Why the other options are wrong
- A. Azure Data Lake Storage Gen2 can store PDFs, but it does not inherently offer advanced search capabilities on document content or metadata without additional services.
- B. Azure Cosmos DB (MongoDB API) is a NoSQL document database, good for metadata, but not natively designed for full-text search within embedded PDF content.
- C. Azure SQL Database is for structured relational data and not optimal for full-text search within PDF documents.
Azure Cognitive Search
A cloud search service that gives developers APIs and tools for adding a rich search experience to their applications.
- Provides full-text search, faceted navigation, and geospatial search.
- Can index various data sources, including structured data, Blob Storage (for PDFs), and databases.
- Integrates AI capabilities for enriching content, such as entity recognition and sentiment analysis.
Memory trick: Cognitive Search for Content and Context