The solution below assumes that you have access to a Microsoft Azure account and an Azure subscription with credits available for testing services. If you are on a trial account, you will not be able to build the cluster due to core quota limits. You can request an increase in that quota as long as you have a pay-as-you-go subscription set up.

To use a free account to create the Azure Databricks cluster, before creating the cluster, go to your profile and change your subscription to pay-as-you-go. For more information, see Azure free account.

Creating a Databricks Workspace

Creating an Azure Databricks workspace involves several steps. In this detailed step-by-step guide, I’ll walk you through the process, including creating a Databricks workspace, configuring settings, and accessing it. Please note that you’ll need an Azure account and appropriate permissions to follow these steps.
Step 1: Sign in to Azure Portal

• Open a web browser and go to the Azure Portal.
• Sign in to your Azure account.

Step 2: Create a New Azure Databricks Workspace

• Once you’re logged in, click the “+ Create a resource” button on the left-hand side or navigate to the “Create a resource” section.

• In the search bar, type “Azure Databricks” and select “Azure Databricks” from the list of results.
• Click the “Create” button to start the Azure Databricks workspace creation process.

Step 3: Configure the Databricks Workspace

• In the “Basics” tab of the “Create Azure Databricks Workspace” wizard, configure the following settings:
• Workspace name: Enter a unique name for your Databricks workspace.
• Subscription: Select your Azure subscription.
• Resource group: Create a new resource group or select an existing one. A resource group is a logical container for your Azure resources.

If you do not have an existing resource group to use, click ‘Create new’. A resource group is a logical container to group Azure resources together. Name it something like ‘intro-databricks-rg’. Next, enter a workspace name. Remember to always stick to naming standards when creating Azure resources, but for now enter whatever you would like. You can keep the location as whatever comes default, or switch it to a region closer to you. For the pricing tier, select ‘Trial’. Finally, select ‘Review and Create’. We can skip networking and tags for now, which are for more advanced set-ups.

• Region: Choose the Azure region where you want to create the workspace.
• In the “Workspace configuration” section, you can select your preferred pricing tier, which determines the capacity and features of your Databricks workspace.
• In the “Virtual Network” section, you can choose to deploy your workspace inside a Virtual Network (VNet) for enhanced network security. You can configure the VNet settings here if needed.
• Review the other settings and ensure they meet your requirements.
• Click the “Next: Networking” button to proceed to the networking configuration. You can configure virtual network settings and firewall rules if necessary.
• Click the “Next: Advanced” button to proceed to the advanced settings, where you can configure additional options like encryption and tags.
• After configuring all the settings, review them, and click the “Review + create” button to validate your configuration.

Step 4: Review and Create

• In the “Review + create” tab, review your configuration to ensure everything is correct.
• Click the “Create” button to start the deployment of your Azure Databricks workspace. Azure will now create the workspace and its associated resources.

Step 5: Wait for Deployment

• The deployment process may take a few minutes. You can monitor the deployment progress in the Azure Portal.

Step 6: Access Your Azure Databricks Workspace

• Once the deployment is complete, navigate to the Azure Databricks workspace in the Azure Portal.
• Click on the workspace to access it. You may need to sign in with your Azure credentials.

Step 7: Configure Users and Permissions

• Inside your Azure Databricks workspace, you can configure user access and permissions. You can invite users, assign roles, and manage access to notebooks and resources within the workspace.

Step 8: Start Using Azure Databricks

• You can start using your Databricks workspace to create and run notebooks for data analysis, build data pipelines, and perform various data-related tasks.