Migrating your analytical workloads to Azure using Synapse Analytics

Microsoft provides you with the ability to migrate your analytical workload to Microsoft Azure by the Azure Synapse Analytics solution introduced by Microsoft Azure.
Azure Synapse Analytics is a comprehensive analytical solution with data warehouse, big data analytics, data integrations and visualization capabilities. You can imagine the Azure Synapse analytics as a SQL Server database for data warehousing, Apache Spark for big data analytics, Azure Data Factory for Extract, Transform and Load (ETL) operations, Power BI for data visualization and Azure Data Explorer for log and time series analysis in one solution!

Azure Synapse SQL component provides us with both Serverless resource model for unplanned workload types and Dedicated resource model for predictable workload types. Both models can integrate with the Azure AI and Machine Learning models.

The Apache Spark for Synapse is used for analyzing the data that is stored locally in the data warehouse, or in other data sources, such as Data Lake or Cosmos DB, using Apache Spark open-source data engine, with the ability to use the Spark Machine Learning algorithms to perform advanced data analysis.

Rather than using a separate ETL tool, you can use the integrated Azure Data Factory functionalities within the Synapse Pipelines to perform the data movement and transformation processes.

Also, you can use the Azure Synapse Data Explorer to query the logs and telemetry data, with powerful indexing technology using Kusto queries.
All these components can be accessed and used within a single user experience called the Synapse Studio: