What are features of Azure Analysis Services?

Azure Synapse Analytics (formerly SQL Data Warehouse): It is an integrated analytics service that brings together big data and data warehousing. It allows you to analyze large volumes of data using either on-demand or provisioned resources. Azure Data Lake Storage: A scalable and secure data lake solution for big data analytics. It allows you to run big data analytics and provides massively parallel processing support. Azure Databricks: An Apache Spark-based analytics platform optimized for Azure. It facilitates the collaborative development of big data and machine learning applications. Azure Stream Analytics: A real-time analytics service that allows you to process and analyze streaming data from devices, sensors, social media, and other sources. Azure HDInsight: A cloud-based service that makes it easy to process large amounts of data using popular open-source frameworks such as Hadoop, Spark, Hive, HBase, and more. Azure Machine Learning: While not exclusively an analytics service, it is often used for predictive analytics and machine learning tasks. It provides tools and services to build, deploy, and manage machine learning models. Azure Data Factory: A cloud-based data integration service that allows you to create data-driven workflows for orchestrating and automating data movement and data transformation. Keep in mind that Microsoft Azure is continuously evolving, and new services or updates to existing services may have been introduced since my last update. I recommend checking the official Azure documentation or Microsoft's Azure website for the most current and detailed information on Azure Analytics Services.