Defining Calculations in SQL Server Analysis Services Multidimensional Modeling

This document guides you through the process of defining calculations in SQL Server Analysis Services (SSAS) multidimensional models. Calculations are essential for deriving new information from your data, such as ratios, variances, and aggregated values that are not directly present in your source data.

Understanding Calculation Types

SSAS supports various types of calculations, primarily categorized into:

Measures

Measures are the quantitative values in your cube that users can aggregate and analyze. They are typically derived from fact tables in your data warehouse. While basic aggregation (SUM, COUNT, AVERAGE) is common, measures can also be defined using MDX expressions for more complex scenarios.

Calculated Members

Calculated members are members that you define within a dimension or a measure group using MDX expressions. They allow you to create new perspectives or derive specific data points without altering the underlying schema. Common uses include:

Creating year-over-year comparisons.
Calculating percentage of total.
Defining conditional aggregations.
Creating custom hierarchies.

Keywords and Functions in MDX

Multidimensional Expressions (MDX) is the query language used to interact with SSAS cubes. Understanding key MDX functions and keywords is crucial for defining powerful calculations:

Aggregate Functions: SUM(), COUNT(), AVG(), MIN(), MAX().
Set Functions: { } (set constructor), { ... ON COLUMNS }, { ... ON ROWS }.
Member Functions: StrToMember(), MemberToStr().
Numeric Functions: IIF(), CASE statements.
Time-Based Functions: ParallelPeriod(), DateAdd().

Creating Calculated Members

You can create calculated members using SQL Server Management Studio (SSMS) or SQL Server Data Tools (SSDT). The process generally involves:

Navigating to the cube designer.
Right-clicking on the dimension or measure group where you want to add the calculated member.
Selecting "New Calculated Member".
Providing a name for the calculated member.
Writing the MDX expression in the formula editor.
Specifying formatting and evaluation properties.

Example: Year-over-Year Sales Growth

Let's define a calculated member for Year-over-Year (YoY) sales growth in the 'Sales' measure group, assuming a 'Date' dimension with a 'Calendar Year' level.

Name: YoY Sales Growth

Formula:


([Measures].[Sales Amount] - ([Measures].[Sales Amount], ParallelPeriod([Date].[Calendar Year].[Calendar Year], 1, [Date].[Calendar Year].CurrentMember))) / ([Measures].[Sales Amount], ParallelPeriod([Date].[Calendar Year].[Calendar Year], 1, [Date].[Calendar Year].CurrentMember))

This formula calculates the difference between the current year's sales and the previous year's sales, then divides by the previous year's sales to get the growth percentage. Ensure you handle cases where the previous year's sales might be zero or null to avoid division by zero errors.

Note: It's good practice to create calculated members on the measure side for aggregatable values like sales, and within dimensions for hierarchical or comparative analysis.

Calculated Measures vs. Calculated Members

While both allow for custom calculations, there's a distinction:

Calculated Measures are typically defined at the cube level and can be thought of as pre-calculated measures. They are evaluated once during cube processing and stored.
Calculated Members are defined within dimensions or measure groups and are evaluated dynamically when a query is run. This offers more flexibility but can impact query performance if not optimized.

Performance Considerations

Complex MDX calculations can impact query performance. Consider the following:

Simplify MDX: Write concise and efficient MDX expressions.
Pre-aggregate Data: For frequently used complex calculations, consider pre-aggregating the results in your data warehouse or as materialized views before loading into SSAS.
Scope and Context: Understand how the context of your calculation affects its evaluation. Use SCOPEx() functions sparingly.
Caching: SSAS caching mechanisms can help improve performance for repeated calculations.

Best Practices

Naming Conventions: Use clear and descriptive names for your calculations.
Documentation: Document your complex MDX formulas within the MDX script or in external documentation.
Testing: Thoroughly test all calculations with various scenarios to ensure accuracy.
User Permissions: Control access to sensitive calculations through security roles.

Tip: Use the MDX query designer in SSMS to test your MDX formulas interactively before deploying them to your cube.

By mastering the definition and implementation of calculations in SSAS multidimensional models, you can unlock deeper insights and provide users with more powerful analytical capabilities.