Querying Models in Azure Analysis Services

This document provides a comprehensive guide to querying data from models deployed in Azure Analysis Services. We will cover the primary query languages, best practices, and available tools to effectively retrieve insights from your analytical data.

Introduction

Azure Analysis Services is a fully managed Platform as a Service (PaaS) that provides enterprise-grade data modeling capabilities. Once you have a semantic model deployed, the next crucial step is to query that model to extract meaningful data for reporting and analysis. This section focuses on how to connect to your Azure Analysis Services tabular or multidimensional models and retrieve data using standard query languages.

Query Languages

Azure Analysis Services supports two primary query languages, depending on the type of model you are working with:

• DAX (Data Analysis Expressions): Primarily used for querying tabular models. DAX is a powerful formula expression language that allows for complex data analysis and retrieval.
• MDX (Multidimensional Expressions): Primarily used for querying multidimensional models. MDX is a query language designed for OLAP (Online Analytical Processing) cubes.

Using DAX

DAX is the preferred language for tabular models in Azure Analysis Services. It offers a rich set of functions and operators to perform sophisticated data manipulation and aggregation. You can write DAX queries to:

• Retrieve specific columns and rows.
• Perform aggregations (SUM, AVERAGE, COUNT, etc.).
• Implement complex calculations using measures.
• Filter data based on various criteria.
• Create dynamic reports and dashboards.

Example DAX Query:

EVALUATE
    CALCULATETABLE (
        Sales,
        Dates[Year] = 2023,
        Products[Category] = "Electronics"
    )

Using MDX

MDX is used when working with multidimensional models. It allows you to navigate through the hierarchical structures of your cubes, slice and dice data, and perform complex aggregations. Key aspects of MDX querying include:

• Selecting cells from the cube.
• Specifying axes (Rows, Columns, Slicers).
• Referencing members, tuples, and sets.
• Using functions for calculations and data manipulation.

Example MDX Query:

SELECT
    {[Measures].[Sales Amount]} ON COLUMNS,
    NON EMPTY {[Product].[Category].Members} ON ROWS
FROM [AdventureWorks]
WHERE ([Date].[Calendar Year].&[2023])

Tooling for Querying

Several tools can be used to connect to and query your Azure Analysis Services models:

• SQL Server Management Studio (SSMS): A versatile tool that supports connecting to Azure Analysis Services and executing both DAX and MDX queries.
• Visual Studio with Analysis Services projects: Useful for developing and testing queries during the model design phase.
• Power BI Desktop: Allows direct connection to Azure Analysis Services models and enables users to build interactive reports and dashboards using DAX.
• Excel (Power Pivot): Can connect to Analysis Services models to leverage data for spreadsheet-based analysis.
• Client libraries: For programmatic access, you can use ADOMD.NET, AMO (Analysis Management Objects), or TOM (Tabular Object Model) in your applications.

Connecting with SSMS:

To connect using SSMS:

1. Open SSMS and select Analysis Services as the server type.
2. Enter the server name for your Azure Analysis Services instance (e.g., asazure://westus.asazure.windows.net/your_server_name).
3. Authenticate using your Azure Active Directory credentials.
4. Once connected, you can open a new query window (DAX or MDX) and execute your queries against the deployed models.

Understanding how to query your Azure Analysis Services models is fundamental to unlocking the value of your data. By leveraging DAX or MDX with the right tools, you can gain deep insights and drive informed business decisions.