MDM Calculations

Calculations are the core of providing business logic and advanced analytical capabilities within your Analysis Services multidimensional models. They allow you to define custom measures, ratios, and complex aggregations that go beyond simple sums or averages.

Understanding Calculation Concepts

In Analysis Services, calculations are typically implemented using MDX (Multidimensional Expressions). MDX is a query language designed for querying and manipulating multidimensional data.

Key Components of MDX Calculations:

• Measures: While basic measures are usually derived directly from fact tables, calculated measures are defined using MDX.
• Calculated Members: These are dynamic members created on the fly within a query, often used for ad-hoc analysis.
• Sets: MDX allows you to define and manipulate sets of members, crucial for complex calculations.
• Tuples: A tuple represents a unique combination of members from different dimensions, forming the basis for cell values.

Implementing MDX Calculations

There are two primary ways to implement MDX calculations in Analysis Services:

1. Calculated Measures

Calculated measures are defined at the cube level and are available for use in any query against that cube. They are stored within the cube definition.

Example: Profit Margin Calculation

Let's assume you have measures for Sales and Cost. A common calculated measure is Profit Margin:

CREATE MEMBER CURRENTCUBE.[Measures].[Profit Margin] AS
    IIF(
        [Measures].[Sales] = 0,
        NULL,
        ([Measures].[Sales] - [Measures].[Cost]) / [Measures].[Sales]
    ),
FORMAT_STRING = '0.00%'

2. Calculated Members

Calculated members are typically defined within an MDX query itself, making them temporary and specific to that query's context.

Example: Year-over-Year Sales Growth

To calculate the Year-over-Year (YoY) sales growth for a specific year:

WITH MEMBER
    [Date].[Calendar Year].&[2023].[Sales YoY Growth] AS
        ([Measures].[Sales], [Date].[Calendar Year].&[2023]) - ([Measures].[Sales], [Date].[Calendar Year].&[2022]),
    FORMAT_STRING = '#,##0'
SELECT
    {[Measures].[Sales], [Date].[Calendar Year].&[2023].[Sales YoY Growth]} ON COLUMNS,
    [Product].[Category].[Category].MEMBERS ON ROWS
FROM
    [YourCubeName]
WHERE
    ([Date].[Calendar Year].&[2023])

Common MDX Functions for Calculations

• SUM(): Sums values.
• AVG(): Calculates the average.
• COUNT(): Counts members or rows.
• IIF(): Conditional logic (if-then-else).
• FORMAT(): Formats values.
• TOPN(), BOTTOMN(): Returns top or bottom members.
• LAG(), LEAD(): Accesses previous or next members in a set.
• PARALLELPERIOD(): Returns a member from a parallel period.

Best Practices for MDX Calculations

• Performance: Keep calculations as simple as possible. Avoid unnecessarily complex MDX or recursive calculations if simpler alternatives exist.
• Readability: Use meaningful names for calculated members and measures. Add comments to your MDX code.
• Context Awareness: Understand the context in which your MDX will be evaluated. Use functions like StrToMember and StrToSet carefully.
• Leverage Aggregations: Ensure your underlying cube design supports efficient aggregation for the measures used in your calculations.
• Testing: Thoroughly test your calculations with various scenarios and data subsets.

Conclusion

Mastering MDX calculations is essential for unlocking the full potential of your SQL Server Analysis Services multidimensional models. By effectively defining calculated measures and members, you can provide powerful insights and drive informed business decisions.