Azure Synapse Analytics Workspaces Experience

Azure Synapse Analytics is a one-stop-shop for analytics aimed at users of various levels, it combines big data and data warehousing capabilities. As someone who has been working in the data analytics space since 2011, I believe that Azure Synapse Analytics is a game-changer.

Microsoft has released Azure Synapse Analytics and the new experience is through workspaces. There is some documentation already available on this topic. (Check this link)

The following image shows just how promising the service will be:

Azure Synapse Analytics Components

Amazing, right?

This picture gives us a lot of information about the features of Azure Synapse Analytics, but let’s take a closer look at the key components:

Azure Synapse Analytics Studio 

This is where everything comes together, and it is our Azure Synapse Analytics Workspace presentation layer. This layer allows us to explore, develop, orchestrate, monitor and manage Azure Synapse Analytics, from Azure Data Factory Pipelines and Power BI reports to Notebooks.

Platform 

Languages: the existing benefits of using SQL for coding will be available as well as the addition of Python, .NET, Java, Scala and R for users who are more comfortable using these languages.

  • Languages:
    SQL
  • Python
  • .NET
  • Java
  • Scala
  • R
  • KSQL

Form Factors 

Provisioned:  Resources are already assigned to the service and running.

ON-Demand: Services for answering business questions are accessible just when you need them.

Analytic Runtimes

SQL: This is the current GA Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse).

Spark: Adding Spark allows the service to run big data analytics workloads using Python, Scala, R and .Net.

Azure Data Explorer:  it makes it easy to analyze high volumes of data in near real time.

Data Integration Layer 

Azure Data Factory will be commonly used for data integration.

Azure Data Lake Storage 

Taking advantage of the existing features of Azure Data Lake Storage and bringing Common Data Models (CMD) to the platform will help to reduce the gap between the Power Platform and Azure Data Services.

Final Thoughts

Without a doubt, Azure Synapse Analytics is exciting and should reshape the data analytics space.

While Microsoft hasn’t released the date for the next milestone (GA) yet, I feel confident that this announcement will happen sometime soon. Just by looking at when the information about creating the services was published, we can gain some insight. It’s also possible to track changes in GitHub: https://github.com/microsoft/azure-docs/commits/master/articles/synapse-analytics

What’s next?

In upcoming blog posts, you will find more information about this exciting service and the different components that make up the new workspace experience for Azure Synapse Analytics.

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