Microsoft Azure Solutions Architect Expert AZ-305 Practice Question
Your company's data platform ingests 5 TB of JSON telemetry every day from IoT devices into Azure Data Lake Storage Gen2 in Parquet format after the initial landing. Data engineers must run large-scale transformations by using Spark notebooks, while business analysts need to run ad-hoc queries over the same data with familiar T-SQL syntax from Power BI. The solution must minimize infrastructure management and deliver both capabilities within a single service. Which Azure service should you recommend?
Azure Synapse Analytics workspace with built-in serverless SQL pool and Apache Spark
Azure HDInsight Spark cluster integrated with Hive Metastore
Azure SQL Managed Instance with PolyBase external tables
Azure Synapse Analytics provides an integrated workspace that includes both Apache Spark pools for data engineering workloads and a serverless SQL pool that lets analysts query data in Azure Data Lake Storage by using standard T-SQL. Because the compute clusters are fully managed and can start on demand, there is little operational overhead.
Azure HDInsight can host Spark, but it requires you to provision and manage clusters and does not provide a built-in T-SQL endpoint for lake queries. Azure SQL Managed Instance is optimized for relational workloads; although external tables can access files in storage, it lacks Spark and is not ideal for petabyte-scale lake analytics. Azure Stream Analytics is a real-time event-processing engine and neither hosts Spark nor supports interactive T-SQL querying of historical data. Therefore, Azure Synapse Analytics best satisfies all the stated requirements.
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Microsoft Azure Solutions Architect Expert AZ-305
Design data storage solutions
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