Azure Synapse Analytics - Create A Synapse Workspace

In this article, we’ll learn to create a synapse workspace in Azure. I’ve created an entire series on Azure Synapse Analytics. This article more so is a pre-requisite for the Azure Cognitive Services Series on Sentiment Analysis. Moreover, you can also learn from this article to perform numerous tasks and explore the other functionalities of Azure.

Azure Synapse Analytics

Azure Synapse is a limitless enterprise analytics service that enables us to get insight from data analytics and data warehousing. Using dedicated resources or serverless architecture, data can be queried and provides scalability as per the increase in the size of the data. You can learn more about it from the series.

  1. Azure Synapse Analytics
  2. Azure Synapse Analytics – Create a Synapse Workspace
  3. Azure Synapse Analytics - Create Dedicated SQL Pool
  4. Azure Synapse Analytics - Creating Firewall at Server-level
  5. Azure Synapse Analytics - Connect, Query and Delete Data Warehouse SQL Pool
  6. Azure Synapse Analytics – Load Dataset to Warehouse from Azure Blob Storage
  7. Azure Synapse Analytics - Best Practices to Load Data into SQL Pool Data Warehouse
  8. Azure Synapse Analytics – Restore Point
  9. Azure Synapse Analytics – Exploring Query Editor
  10. Azure Synapse Analytics – Automation Task
  11. Azure Synapse Analytics – Machine Learning

Now, let us learn to create a synapse workspace in Azure Synapse Analytics.

Step 1

First of all, login to the Azure Portal. You’d need a paid subscription or sponsorship pass in order to create a Synapse Workspace. The Sandbox from Microsoft Learn will not support.

Step 2

Search for Azure Synapse Analytics in the Search Bar. Select the Azure Synapse Analytics from the Drop Down.

Step 3

Now, we’ll learn taken to the Azure Synapse Analytics page. Click on Create Synapse Workspace.

Step 4

Now we’ll be provided with the details to fill in.

Select the Subscription you are using. Here, I’m using an Azure Pass Sponsored Subscription. Learn more about redeeming Azure Pass from the previous article, How To Redeem Azure Pass?

Now, for resource group, you might need to Create one if you already haven’t created any resources in Azure. Click on Create new and type in the name.

Step 5

Next, we need to add in Workspace name where we’ll have the Data Lake Storage Gen2. The Data Lake is the location where we’ll add datasets in order to function any queries and even machine learning training and predictions.

Remember, there are a few criteria you need to fulfill in order to set in the workspace name.

Next, add the region. Mostly, US locations like Central US, East US would be best. Next, I’ve now named my Data Lake Storage Gen2 Account as dlg2ojash and File System name as ‘user’.

Once done, click on Security.

Step 5

Add in the SQL administrator credentials if you want to secure the workspace. For now, it isn’t so required.

Now, click on Review + Create

Step 6

As the Validation is successful, we’ll be provided with the option to Create. Click the Click Button.

The notification will pop up as the submission for deployment is initiated.

Step 7

Now, we can see the deployment is in progress.

As resources are created during the deployment process, we can see the Status update.

Step 8

Finally, as the Deployment is complete, we can visit the Resource Group.

Here, on the resource group page we can see the link to data lake storage and Synapse Workspace.

Click the Synapse Workspace, here named ojashworkspace.

Step 9

The Synapse Workspace page is opened. Now, by clicking on the Workspace Web URL we can access the Synapse Workspace.

Step 10

We can then use this resource group we created for Synapse Workspace to create numerous other services.

If we want to delete the workspace, we can simply select the Workspace and Click on Delete for Delete the entire Resource Group from the option in the Menu.

Here, to delete the resource, we type in the resource group name and then click on Delete.

Similarly, we can also explore individual services like the Data Lake Storage and Delete them.

This will make sure; we aren’t charged for unused services. It is a wise habit to pause when the services aren’t required and to delete them and resource groups as the tasks are completed to save from any unwanted charges to incur.


Thus, in this article, we learned in step-by-step process to Create a Synapse Workspace in Azure Synapse Analytics. We’ll further expand and use this workspace to explore different services of Azure focused in Machine Learning through Azure Cognitive Services such as Sentiment Analysis, Anomaly Detection, and more.