What is Azure Synapse Analytics?

Azure Synapse Analytics was announced in the fall of 2019. The Microsoft product is the next generation of SQL Data Warehouse, and is designed to bring data warehousing and big data together for more comprehensive analysis.

Azure Synapse Analytics is able to ingest data from over 95 data connectors, empowering users to collect, group, and analyze data from disparate systems.

For more information on how Azure Synapse Analytics works, visit our recent article that explains the technology.
 

What are some key features of Azure Synapse Analytics?

Here are some new features beyond what was generally available in SQL Data Warehouse. A more complete list of all features can be found in Microsoft’s documentation.
 

• The Azure Synapse Studio is a unified workspace for all data professionals using the Synapse Analytics service. Data scientists, data engineers, DBAs, and business analysts are all able to carry out tasks on both relational and unstructured data using standard SQL.
• The PREDICT function is now available for analysts to generate a predicted value or scores based on a model (in preview).
• Direct streaming ingestion offers real time data streaming and the ability to run queries over the live stream (in preview).
• ParquetDirect technology uses an integrated Spark engine built into Synapse, not Databricks, to query the data lake directly. It natively interacts with files stored in the Apache Parquet columnar format (in preview).
• Workload isolation provides the ability to define workload groups and reserve resources for priority workloads (in preview).
• SQL Server Data Tools (SSDT) Support for continuous integration and deployment (CI/CD).

Who is Azure Synapse Analytics designed for?

Azure Synapse Analytics is designed for businesses (primarily enterprises and large organizations) of various industries, such as manufacturing, retail, financial services, and healthcare. Professionals ranging from data scientists to business analysts can all benefit from the technology.
 

What is Azure Synapse Analytics?

Azure Synapse Analytics was announced in the fall of 2019. The Microsoft product is the next generation of SQL Data Warehouse, and is designed to bring data warehousing and big data together for more comprehensive analysis.

Azure Synapse Analytics is able to ingest data from over 95 data connectors, empowering users to collect, group, and analyze data from disparate systems.

For more information on how Azure Synapse Analytics works, visit our recent article that explains the technology.

What are some key features of Azure Synapse Analytics?

Here are some new features beyond what was generally available in SQL Data Warehouse. A more complete list of all features can be found in Microsoft’s documentation.
 

• The Azure Synapse Studio is a unified workspace for all data professionals using the Synapse Analytics service. Data scientists, data engineers, DBAs, and business analysts are all able to carry out tasks on both relational and unstructured data using standard SQL.
• The PREDICT function is now available for analysts to generate a predicted value or scores based on a model (in preview).
• Direct streaming ingestion offers real time data streaming and the ability to run queries over the live stream (in preview).
• ParquetDirect technology uses an integrated Spark engine built into Synapse, not Databricks, to query the data lake directly. It natively interacts with files stored in the Apache Parquet columnar format (in preview).
• Workload isolation provides the ability to define workload groups and reserve resources for priority workloads (in preview).
• SQL Server Data Tools (SSDT) Support for continuous integration and deployment (CI/CD).

Who is Azure Synapse Analytics designed for?

Azure Synapse Analytics is designed for businesses (primarily enterprises and large organizations) of various industries, such as manufacturing, retail, financial services, and healthcare. Professionals ranging from data scientists to business analysts can all benefit from the technology.