SSAS Measures and Calculations

Microsoft SQL Server Analysis Services Documentation

Understanding Measures and Calculations in SQL Server Analysis Services

This article delves into the fundamental concepts of measures and calculations within SQL Server Analysis Services (SSAS). Measures are aggregatable numerical values that users analyze, such as sales amount, quantity sold, or profit. Calculations, on the other hand, extend these basic measures by performing complex computations and aggregations using Multidimensional Expressions (MDX) or DAX (Data Analysis Expressions).

What are Measures?

Measures are typically derived from fact tables in your data warehouse. They represent the business metrics you want to track and analyze. In SSAS, measures are defined within a cube or tabular model and can be aggregated using various functions like SUM, COUNT, MIN, MAX, and AVG.

Key characteristics of measures:

  • They are numerical values.
  • They are aggregatable.
  • They are the primary objects of analysis.

Creating Basic Measures

When you build a cube or tabular model, SSAS often automatically creates measures for numerical columns in your fact tables. You can also manually create measures to define specific aggregations.

For example, to create a measure for total sales amount:


-- In SSAS Multidimensional Model Designer
CREATE MEASURE [Measures].[Sales Amount] AS SUM([SalesOrderDetail].[LineTotal])

Calculated Measures and Named Calculations

Calculated measures allow you to create new measures based on existing measures or other calculated members. Named calculations are expressions that are evaluated at query time but are not explicitly stored as measures.

MDX Calculations

MDX is a query language used with SSAS Multidimensional models. It's powerful for defining complex calculations, including:

  • Calculated Members: Members that are not physically stored but are calculated on the fly.
  • Parent-Child Hierarchies: Calculations involving relationships within a hierarchy.
  • Time-Intelligence Functions: Calculations for year-to-date, prior period comparisons, etc.

Example of an MDX calculated member for Profit Margin:


WITH MEMBER [Measures].[Profit Margin] AS
    ([Measures].[Profit] / [Measures].[Sales Amount]) * 100
SELECT
    [Measures].[Profit Margin] ON 0,
    [Date].[Calendar Year].Members ON 1
FROM [Adventure Works Cube]

DAX Calculations (Tabular Models)

DAX is used in SSAS Tabular models and Power BI. It offers a more spreadsheet-like syntax and is very efficient for in-memory analytics.

  • Calculated Columns: New columns added to a table based on expressions.
  • Measures: Similar to SSAS Multidimensional measures, but defined using DAX.

Example of a DAX measure for Profit Margin:


Profit Margin = DIVIDE([Total Profit], [Total Sales Amount]) * 100
Important: Understanding the distinction between MDX and DAX is crucial, as they are used in different SSAS modeling paradigms (Multidimensional vs. Tabular). While the concepts of measures and calculations are similar, the syntax and implementation differ significantly.

Common Calculation Scenarios

  • Year-to-Date (YTD) Sales: Calculating cumulative sales from the beginning of the year to the current date.
  • Average Sales per Order: Calculating the average value of each sales order.
  • Growth Rates: Comparing current period performance to previous periods.
  • Ratios and Percentages: Expressing one measure as a proportion of another.

Best Practices

  • Keep calculations as simple as possible for performance.
  • Use descriptive names for measures and calculations.
  • Leverage built-in MDX and DAX functions for common scenarios.
  • Test your calculations thoroughly with various data subsets.

Mastering measures and calculations is essential for unlocking the full analytical power of SQL Server Analysis Services and providing meaningful insights to your business users.