Microsoft Certified: Azure Fundamentals (AZ-900) 2026 – 400 Free Practice Questions to Pass the Exam

The most appropriate Azure solution for querying and transforming data for insights is Data Lake Analytics. This service is specifically designed to handle large-scale data processing and analytics. It allows users to run queries using a variety of languages such as U-SQL, an SQL-like language that integrates the concepts of SQL with C#. This capability makes it well-suited for transforming large datasets stored in Azure Data Lake Storage and enables users to extract valuable insights efficiently.

Data Lake Analytics provides a serverless approach, meaning that users pay only for the resources they consume during their analytics jobs, which can help manage costs associated with data processing tasks. It also integrates seamlessly with other Azure services, facilitating the end-to-end analytics workflow from data ingestion to transformation and visualization.

While other options like CosmosDB and Azure SQL Database are powerful for managing structured and unstructured data, they are primarily databases rather than analytics platforms focused on large-scale transformation and insightful querying. Blob Storage serves as a storage solution for unstructured data but does not provide built-in analytics capabilities. Therefore, Data Lake Analytics stands out as the suitable choice for this use case.