Microsoft Azure Solutions Architect Expert AZ-305 Practice Question
Your company stores transactional data in an on-premises SQL Server 2019 instance. About 80 GB of new and updated rows are produced daily. Analysts must load this data each night into a dedicated SQL pool in Azure Synapse Analytics, cleansing and aggregating it by product category. You need a solution that minimizes custom code and administration effort and can easily incorporate other data sources in the future. Which Azure service or feature should you use to implement the nightly pipeline?
Azure Synapse Link for SQL combined with Power BI dataflows for transformations
Azure Data Factory pipeline that uses a self-hosted integration runtime and Mapping Data Flows
Azure Logic Apps with SQL Server and Synapse connectors to copy and transform the data
Scheduled AzCopy jobs to Azure Data Lake Storage followed by Azure Functions for transformations
Azure Data Factory (ADF) is Microsoft's recommended code-free ETL service. A self-hosted integration runtime enables secure, high-throughput copying from on-premises SQL Server to the cloud, and Mapping Data Flows provide Spark-based transformations such as cleansing and aggregations without writing custom code. The built-in scheduler orchestrates the nightly load and can be extended to additional sources.
Azure Logic Apps focus on event-driven workflows and are not optimized for moving tens of gigabytes of data. Combining AzCopy with Azure Functions would require significant scripting and operational overhead. Azure Synapse Link for SQL currently supports Azure SQL Database and SQL Server 2022 (preview) but not SQL Server 2019, so it cannot meet this requirement.
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Microsoft Azure Solutions Architect Expert AZ-305
Design data storage solutions
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