Cloud platform for data analytical workloads through support for multiple data storage, processing, and analysis technologies in a single, integrated solution.
Data files are stored and processed inside a data lake. By default it is linked to an Azure Data Lake Storage Gen2 container, but you can link multiple data lakes that are based on different storage platforms.
Ingesting and Transforming Data with Pipelines
Azure Synapse Analytics has a built-int support for creating, running, and managing pipelines that orchestrate the ETL process.
Info
Azure Synapse Analytics uses the same pipeline technology as Azure Data Factory.
Querying and Manipulating Data
Supports SQL-based data querying and manipulation through two kinds of SQL pool that are based on SQL Server:
- A built-in serverless pool that is optimized for using relational SQL semantics to query file-based data in a data lake.
- Custom dedicated SQL pools that host relational data warehouses.
Processing and Analyzing Data with Apache Spark
Create one or more Spark pools and use interactive notebooks to combine code and notes as you build solutions for data analytics, machine learning, and data visualization.
Data Explorer
Based on Azure Data Explorer service (the same as in Azure CosmosDB Data Explorer) and utilizes Kusto Query Language (KQL).
Demo
- Register required service providers (
Microsoft.Synapse,Microsoft.Sql,Microsoft.Storage,Microsoft.Compute) - Create new RG
- Create Azure Synapse Analytics Workspace with data lake, sql pool, and apache spark pool