SQL Server Analysis Services (SSAS) is a powerful tool for Online Analytical Processing (OLAP) workloads. With the advent of the Azure cloud, Azure Analysis Services provides an Online Analytical Processing engine on the cloud. In this article, we will explore how to get started with Azure Analysis Services and understand the configuration and pricing options to create our first Analysis Services instance.
Creating an Azure Analysis Services Instance
To create an Azure Analysis Services instance, you need to have an Azure account with the necessary administrative privileges. If you don’t have an Azure account, you can sign up for a free account and avail the $200 credit for first-time users.
Once you have access to an Azure account, follow these steps to create your first Analysis Services instance:
- Log in to your Azure account and navigate to the Azure portal.
- Click on “All Services” or use the search feature to find “Analysis Services”.
- Click on “Analysis Services” to open the dashboard page.
- Click on the “Add” button or “Create analysis services” button to start the instance creation process.
- Provide a unique server name, select the Azure subscription, and choose the resource group for the instance.
- Select the region closest to your physical location.
- Choose the pricing tier based on your requirements. The D1-tier is recommended for learning and evaluation purposes.
- Select the administrator for the server instance.
- Configure the backup storage settings, if required.
- Click on the “Create” button to start the creation process.
Once the instance is created, you can monitor it using the metrics section in the dashboard page. You can also connect on-premise instances and tools with Azure Analysis Services using an On-Premises Data Gateway.
Conclusion
Azure Analysis Services provides a powerful Online Analytical Processing engine on the Azure cloud. In this article, we learned how to create an Azure Analysis Services instance and explored the different configuration options. With Azure Analysis Services, you can leverage the benefits of cloud computing for your OLAP workloads.