can you create calculated tables in ssas multidimensional

3 min read 23-01-2025

can you create calculated tables in ssas multidimensional

Creating calculated tables directly within a SSAS Multidimensional database isn't possible in the same way you would in a SSAS Tabular model. Multidimensional models rely on a different architecture and data processing paradigm. Instead of calculated tables, you achieve similar results using calculated members within dimensions or calculated measures within cubes. Let's explore these alternatives and how they achieve comparable functionality.

Understanding the Differences: Multidimensional vs. Tabular

Before diving into solutions, it's crucial to understand the fundamental difference between SSAS Multidimensional and SSAS Tabular models:

SSAS Multidimensional: This older model uses a MOLAP (Multidimensional Online Analytical Processing) architecture. Data is pre-aggregated and stored in a multidimensional cube. Calculations are performed on the pre-aggregated data.
SSAS Tabular: This newer model utilizes a ROLAP (Relational Online Analytical Processing) or hybrid approach. Data is stored in a columnar format optimized for analytical queries. Calculated tables are a core feature, allowing for dynamic data derivation.

Because of these architectural distinctions, the concept of a "calculated table" doesn't directly translate to the multidimensional world.

Achieving Calculated Table Functionality in SSAS Multidimensional

While you can't create a table in the same way as in Tabular, you can achieve similar results through these methods:

1. Calculated Members within Dimensions

Calculated members allow you to derive values based on existing members within a dimension. This is ideal when you need to create a new category or aggregation based on existing dimensional data.

Example: Imagine a dimension with "Region" members (North, South, East, West). You can create a calculated member "Overall" that sums up the sales from all regions.

MEMBER [Region].[Region].[Overall] AS
SUM( { [Region].[Region].MEMBERS } , [Measures].[Sales] )

This calculated member acts like a new row (or column depending on your cube design) derived from existing data without needing a separate table.

2. Calculated Measures within Cubes

Calculated measures are more powerful and flexible. They allow you to create entirely new metrics based on combinations of existing measures and dimensions.

Example: You might want to calculate a "Profit Margin" measure based on "Sales" and "Cost" measures.

MEMBER [Measures].[Profit Margin] AS
IIF([Measures].[Sales] > 0, ([Measures].[Sales] - [Measures].[Cost]) / [Measures].[Sales], 0)

This creates a new measure directly within the cube, effectively providing data that mimics a calculated table column. You could then use this in your queries and reports as if it were from a distinct table.

3. Views and Stored Procedures (Indirect Approach)

Before the data is loaded into the multidimensional cube, you can leverage SQL Server views or stored procedures to pre-calculate values. The results of these views or stored procedures can then be loaded as fact table data in your cube. This is less dynamic than calculated members or measures but allows complex data transformations beforehand.

Choosing the Right Approach

The best method depends on the complexity of your calculations and how you'll use the resulting data.

Simple aggregations or new categories: Calculated members within dimensions are sufficient.
Complex calculations combining multiple measures: Calculated measures within the cube are necessary.
Extremely complex or pre-processed data: Views and stored procedures are a better solution for pre-calculation.

Limitations Compared to Tabular Calculated Tables

Keep in mind that these methods don't offer the exact same flexibility as calculated tables in SSAS Tabular:

Dynamic updates: Calculated members and measures are typically recalculated during processing. They're not as readily updated as a Tabular calculated table.
Data modeling limitations: Multidimensional models have a different schema structure which may limit the types of calculated results you can easily produce.

Conclusion

While you can't directly create calculated tables in SSAS Multidimensional, the alternative techniques of calculated members and measures, along with pre-processing with views and stored procedures, provide effective ways to achieve similar results. Choosing the right approach depends largely on your specific needs and the complexities of your data and calculations. Remember that if flexibility and dynamic calculation are crucial, SSAS Tabular might be a more suitable option for your project.