Azure Synapse Analytics is the correct choice for building a modern data warehouse to store and analyze very large volumes of structured and semi structured information.

Azure Synapse Analytics combines enterprise data warehousing, big data integration, and analytics in a single service. Synapse provides dedicated SQL pools and serverless SQL along with Spark pools so teams can run large scale queries and process both structured and semi structured data efficiently.

Synapse is designed for petabyte scale analytics and it integrates closely with Azure Data Lake Storage for storage and with other Azure services for ingestion and orchestration. Those integrated capabilities make it the best fit when a modern data warehouse is needed.

Azure Data Lake Storage is primarily an object storage service that is optimized for storing massive amounts of raw data. It is not itself a data warehouse because it does not provide the integrated query engines and warehousing features that Synapse offers, although it is commonly used together with Synapse.

Azure SQL Database is a managed relational database service that is optimized for transactional workloads and for smaller scale analytics. It does not natively provide the large scale analytics, big data integration, and mixed workload capabilities required of a modern data warehouse.

Google BigQuery is a highly scalable serverless data warehouse but it is a Google Cloud service and not an Azure offering. The question asks for the best Azure service so BigQuery is not the correct choice here.

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