Getting Started with Azure Analysis Services

Azure Analysis Services (AAS) is a fully managed cloud service that provides enterprise-grade data modeling capabilities. It enables you to build semantic models that can be used across various reporting tools, including Power BI, Excel, and other Microsoft BI products. This article will guide you through the initial steps of setting up and exploring Azure Analysis Services.

What is Azure Analysis Services?

At its core, Azure Analysis Services provides a scalable and robust platform for creating tabular and multidimensional models. These models act as a single source of truth for your business data, simplifying data access and ensuring consistency. Key benefits include:

Performance: Optimized for fast query responses through in-memory caching and columnar storage.
Scalability: Easily scale your resources up or down based on demand.
Integration: Seamlessly integrates with Azure services like Azure Data Factory, Azure Blob Storage, and Power BI.
Security: Robust security features including role-based access and integration with Azure Active Directory.

Prerequisites

Before you begin, ensure you have the following:

An Azure subscription. If you don't have one, you can sign up for a free account.
Permissions to create resources in your Azure subscription.

Step 1: Creating an Azure Analysis Services Instance

Follow these steps to create your first AAS instance:

Navigate to the Azure portal.
Click on "Create a resource".
In the search bar, type "Analysis Services" and select it from the results.
Click "Create".
Fill in the required details:
- Subscription: Select your Azure subscription.
- Resource group: Create a new one or select an existing one.
- Server name: A unique name for your AAS server.
- Location: Choose a region close to your data sources or users.
- Pricing tier: Select a tier based on your performance and capacity needs. For testing, the "Developer" tier is often sufficient.
- Admin: Specify an Azure AD user or group to be the server administrator.
Click "Review + create" and then "Create".

Tip: Choosing the Right Pricing Tier

Azure Analysis Services offers several pricing tiers (Developer, Basic, Standard). The Developer tier is suitable for development and testing, while Basic and Standard tiers are for production workloads. Consider your performance, scalability, and budget requirements when making your selection.

Step 2: Connecting to Your Analysis Services Instance

Once your AAS instance is deployed, you can connect to it using compatible tools. SQL Server Management Studio (SSMS) is a common choice:

Using SQL Server Management Studio (SSMS)

Download and install the latest version of SQL Server Management Studio (SSMS).
Open SSMS.
In the "Connect to Server" dialog, select "Analysis Services" for the "Server type".
Enter your AAS server name (e.g., your-aas-server-name.windows.net).
For "Authentication", choose "Azure Active Directory - Universal with MFA" or another suitable Azure AD option.
Click "Connect".

                
                -- Example of a simple DAX query in SSMS
                EVALUATE
                  CALCULATETABLE (
                    'DimProduct',
                    'DimProduct'[Color] = "Red"
                  )
                
            

Step 3: Creating a Tabular Model

The most common way to work with Azure Analysis Services is by creating tabular models. You can use Visual Studio with the Analysis Services projects extension or directly in SSMS.

Using Visual Studio with Analysis Services Projects

Ensure you have Visual Studio installed.
Install the Microsoft Analysis Services Projects extension from the Visual Studio Marketplace.
In Visual Studio, go to "File" > "New" > "Project".
Under "Analysis Services", select "Analysis Services Tabular Project".
Give your project a name and click "Create".
In the Model Designer, right-click on "Data Sources" and select "New Data Source".
Choose your data source type (e.g., SQL Server, Azure SQL Database) and provide connection details.
Right-click on "Tables" and select "Add Table" to import data from your data source.
Use the "Table Designer" to create relationships, define measures, and create calculated columns.
Once your model is ready, deploy it to your Azure Analysis Services instance by right-clicking the project and selecting "Deploy".

Key Concepts: Tabular Models

Tabular models use DAX (Data Analysis Expressions) for calculations, similar to Excel Power Pivot. They are in-memory, relational databases optimized for analytical workloads.

Conclusion

This guide provided a foundational overview of getting started with Azure Analysis Services. You've learned how to provision an instance, connect to it, and begin building semantic models. From here, you can explore more advanced topics like security roles, query performance optimization, and integration with visualization tools like Power BI.

Next Steps:

Explore DAX Basics for Analysis Services.
Learn about Securing Your Analysis Services Models.
Discover Integrating Power BI with Azure Analysis Services.