AZ-305 Question 85
Single answerYour company collects petabytes of unstructured sensor data from IoT devices. The data must be ingested at high throughput, integrated with Azure Synapse Analytics for big data processing, and support a hierarchical namespace for granular file-level access control. Which of the following storage solutions best meets these requirements?
- A
Azure Data Lake Storage Gen2 with hierarchical namespace enabled
- B
Azure Files with the premium performance tier
- C
Azure SQL Database
- D
Azure Table Storage
Show answer and explanation
Correct answer: A
Explanation
For large-scale unstructured data and advanced analytics, Azure Data Lake Storage Gen2 is the recommended solution. It offers hierarchical namespaces for fine-grained security, integrates with Azure Synapse Analytics, and is designed for high-throughput data ingestion. For more details, refer to Microsoft’s documentation on Azure Data Lake Storage Gen2 at https://learn.microsoft.com/azure/storage/blobs/data-lake-storage-introduction.
- A. Correct.
Azure Data Lake Storage Gen2 supports a hierarchical namespace, large-scale ingestion, and seamless integration with Azure Synapse Analytics. It also provides fine-grained ACLs (access control lists), making it ideal for big data analytics scenarios with unstructured data.
- B. Incorrect.
Azure Files is more suited for shared file storage scenarios (e.g., lift-and-shift of on-premises file shares) rather than large-scale analytics of unstructured data. While it can store files, it does not provide the hierarchical namespace or the native integration with big data processing frameworks required here.
- C. Incorrect.
Azure SQL Database is a relational database service. It is not optimized for massive unstructured data ingestion or hierarchical file access control. It is best suited for structured or relational data with defined schemas.
- D. Incorrect.
Azure Table Storage is a NoSQL key-value store for semi-structured data. It does not offer hierarchical namespace nor direct integration with Synapse for big data analytics at large scale. It is better suited for storing simple key-value entities.