Define Calculations in Multidimensional Models

Calculations in SQL Server Analysis Services (SSAS) multidimensional models allow you to extend your cube's data by deriving new information from existing measures. This includes creating calculated members, calculated measures, and KPIs. These calculations are typically defined using Multidimensional Expressions (MDX).

Understanding Calculation Concepts

Calculated Members

A calculated member is a member of an existing dimension that is computed dynamically. It's useful for representing aggregations, ratios, or comparisons that are not explicitly stored in the data warehouse. For example, you might create a calculated member for "Year-over-Year Growth" within a Time dimension.

Calculated Measures

Calculated measures are new measures defined within a measure group. They are similar to calculated members but are associated with the cube's measures rather than a dimension. Examples include "Profit Margin" (calculated as Profit / Sales) or "Average Order Value".

Key Performance Indicators (KPIs)

KPIs are special types of calculated measures that provide a business-oriented view of performance. They typically include a value, a goal, and a status indicator (e.g., good, bad, neutral). KPIs help users quickly assess performance against targets.

Creating Calculated Members and Measures

Calculations are typically created using the SSAS Multidimensional Model designer in Visual Studio. You can define them in the following locations:

Cube Designer: Within the "Calculations" tab of the Cube Designer, you can define named calculations that can be referenced across the cube.
Dimension Designer: For specific dimension members, you can define calculations directly within the Dimension Designer.

Steps to Create a Calculation

Open your Analysis Services project in Visual Studio.
Navigate to the Cube Designer for the cube you want to modify.
Go to the Calculations tab.
In the toolbar, click New Calculated Member or New Calculated Measure.
Provide a Name for your calculation.
In the Expression box, write your MDX formula.
Optionally, assign a Format String for how the result should be displayed.
Specify the Parent member for calculated members, or the Measure Group for calculated measures.
Click OK.

MDX Syntax for Calculations

The core of defining calculations in SSAS multidimensional models is MDX. Here are some common MDX constructs:

Basic Arithmetic Operations

You can use standard arithmetic operators:

-- Example: Profit Margin
([Measures].[Profit] / [Measures].[Sales])

Referencing Measures and Members

Measures are referenced using the [Measures].[MeasureName] syntax. Dimension members are referenced using [DimensionName].[HierarchyName].[LevelName].[MemberName] or similar structures.

Using Functions

MDX provides a rich set of functions for aggregation, time-series analysis, string manipulation, and more.

SUM(): For summing values.
AVG(): For calculating averages.
IIF(): For conditional logic.
LAG() and LEAD(): For time-series comparisons.

Example: Year-over-Year Growth

This MDX calculates the growth of Sales from the previous year.

WITH MEMBER MEASURES.SalesYoYGrowth AS
  ( ([Measures].[Sales], ParallelPeriod([Date].[Calendar].CalendarYear, 1, [Date].[Calendar].CurrentMember) ) )
  - [Measures].[Sales]
  / [Measures].[Sales]
SELECT
  {[Measures].[Sales], MEASURES.SalesYoYGrowth} ON COLUMNS,
  {[Date].[Calendar].CalendarYear.Members} ON ROWS
FROM [YourCubeName]

Defining KPIs

KPIs provide a high-level view of business performance. They are defined in the Cube Designer's KPI tab.

Key Components of a KPI

Value: The primary measure for the KPI (e.g., Sales).
Goal: A target value for the KPI. This can be a static value, another measure, or a calculated member.
Status: An expression that determines the current status (e.g., good, warning, bad) based on the value and goal.
Trend: An expression that shows the direction of the KPI over time.

Tip: When defining complex calculations, use the MDX script editor in SSAS to leverage IntelliSense and syntax highlighting for better productivity.

Best Practices

Use Clear Naming Conventions: Make calculation names descriptive and consistent.
Optimize MDX: Write efficient MDX queries. Avoid unnecessary complex logic or inefficient function calls.
Leverage Calculated Measures First: Where possible, define calculations as calculated measures rather than complex calculated members within dimensions.
Test Thoroughly: Always test your calculations with various scenarios and data subsets to ensure accuracy.
Document Your Calculations: Add comments to your MDX script or maintain separate documentation to explain the logic behind complex calculations.

Note: The performance of your cube can be significantly impacted by the complexity and efficiency of your MDX calculations.

By effectively defining calculations, you can transform raw data into meaningful business insights, enabling richer analysis and better decision-making within your organization.