Detailed Explanation

When using Azure Cosmos DB with Azure Synapse Link and a full fidelity schema configured for the analytical store, the system maintains strict schema fidelity by tracking data types precisely. This means that fields with the same name but different data types are treated as separate columns in the analytical store.

Analysis of the Documents:

• First document: {"customerID": 12, "customer": "Tailspin Toys"}

  • customerID is an integer (12)
  • customer is a string ("Tailspin Toys")

• Second document: {"customerID": "14", "customer": "Contoso"}

  • customerID is a string ("14")
  • customer is a string ("Contoso")

Column Creation in Analytical Store:

1. customerID_Number column: Created for the integer value 12 from the first document
2. customerID_String column: Created for the string value "14" from the second document
3. customer_String column: Created for the consistent string values ("Tailspin Toys" and "Contoso")

Why This Happens:

The full fidelity schema preserves the original data types from Cosmos DB documents. When the same field name (customerID) appears with different data types (integer vs. string) across documents, the analytical store creates separate columns to maintain data integrity and type safety. This prevents data loss and ensures accurate analytical processing.

Why Other Options Are Incorrect:

• Option A (1): Incorrect because multiple columns are needed to handle different data types
• Option B (2): Incorrect because it doesn't account for the separate columns needed for customerID with different data types
• Option D (4): Incorrect because there are only three distinct field/data type combinations across both documents

This behavior ensures that analytical queries can accurately process data while maintaining the original document structure and data types from Cosmos DB.