AZ-305 Question 78
Single answerA global manufacturing company needs to store billions of semi-structured JSON sensor data records and high-resolution images from their production lines. They want to run Spark-based analytics on this data to perform batch transformations and generate real-time insights. Which of the following data storage options in Azure is the most suitable for cost-effectively handling this large volume of semi-structured and unstructured data while providing a hierarchical namespace and easy integration with big data analytics?
- A
Azure Files
- B
Azure Cosmos DB
- C
Azure Data Lake Storage Gen2
- D
Azure SQL Database
Show answer and explanation
Correct answer: C
Explanation
Azure Data Lake Storage Gen2 is designed to store and analyze huge volumes of data, including semi-structured JSON, logs, images, and more. It combines the scalability of Azure Blob Storage with a hierarchical file system for analytics. According to Microsoft best practices (see https://learn.microsoft.com/azure/storage/blobs/data-lake-storage-introduction), ADLS Gen2 is the recommended solution for big data analytics workflows, offering cost-effective and efficient integration with Spark-based platforms.
- A. Incorrect.
Azure Files is primarily designed for SMB/CIFS file shares and is not the most cost-effective or optimal choice for large-scale analytics scenarios that require hierarchical namespace and big data integration.
- B. Incorrect.
Azure Cosmos DB is a globally distributed, multi-model database well suited for low-latency, high-throughput transactional scenarios. However, storing massive volumes of sensor and image data for big data analytics is generally more cost-effective and flexible with an object store such as Azure Data Lake Storage Gen2.
- C. Correct.
Azure Data Lake Storage Gen2 provides a highly scalable repository for big data analytics, supports hierarchical namespaces, and integrates seamlessly with analytics engines like Azure Synapse and Azure Databricks. This makes it ideal for handling large, unstructured and semi-structured datasets.
- D. Incorrect.
Azure SQL Database is a relational database service. While it can handle structured data efficiently, it is neither cost-effective nor optimal for competitively storing massive unstructured or semi-structured files intended for high-scale analytics.