Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a container named container1 in an Azure Cosmos DB Core (SQL) API account. You need to make the contents of container1 available as reference data for an Azure Stream Analytics job. Solution: You create an Azure Data Factory pipeline that uses Azure Cosmos DB for NoSQL as the input and Azure Blob Storage as the output. Does this meet the goal?

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B. No While Azure Data Factory can copy data from Azure Cosmos DB to Azure Blob Storage, and Blob Storage is a valid source for Azure Stream Analytics reference data, this solution uses a batch process. If the requirement for making data 'available' implies near real-time synchronization or frequent updates, a batch-oriented data pipeline might not be sufficient for the Stream Analytics job's needs.

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A. Yes This solution would typically be considered viable for making data available for Stream Analytics, but it might not satisfy implicit requirements for immediate data freshness or streaming updates often needed for reference data in real-time processing scenarios.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…

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