Measures in Multidimensional Modeling
Measures are the numerical values that you analyze in a data model. They represent business metrics such as sales amounts, quantity sold, profit, or headcount. In SQL Server Analysis Services (SSAS) multidimensional models, measures are typically stored in measure groups, which are often derived from fact tables in your data warehouse.
What are Measures?
Measures are the core data points that users will query and aggregate. They are typically numeric and represent quantifiable business facts. Unlike dimensions, which provide context, measures provide the values to be analyzed.
Types of Measures
Measures in SSAS can be categorized in several ways:
- Standard Measures: These are direct representations of values from the fact table. For example, a `SalesAmount` column directly from a sales fact table.
- Calculated Measures: These are measures defined by MDX (Multidimensional Expressions) or DAX (Data Analysis Expressions) formulas. They can perform calculations on other measures or attributes.
Measure Groups
Measures are organized into measure groups. A measure group typically corresponds to a fact table in the underlying data source. Each measure group can contain one or more measures.
Best Practice: Group related measures together. For example, all measures related to sales (e.g., Sales Amount, Sales Quantity, Discount Amount) should be in a 'Sales' measure group.
Creating and Configuring Measures
When you create a measure group from a fact table, Analysis Services automatically creates measures for each numeric column in the fact table. You can then configure these measures:
- Name: A user-friendly name for the measure.
- Source: The underlying column in the fact table or the MDX/DAX expression.
- Aggregation Function: How the measure should be aggregated across different dimensions (e.g., Sum, Count, Average, Min, Max). The default is usually Sum for numeric columns.
- Format String: Defines how the measure values should be displayed (e.g., currency, percentage, number of decimal places).
Common Aggregation Functions:
Sum: Adds up all values.Count: Counts the number of rows or non-null values.Average: Calculates the average of values.Min: Finds the minimum value.Max: Finds the maximum value.Distinct Count: Counts the number of unique values.
Calculated Measures with MDX
Calculated measures provide powerful analytical capabilities. They are defined using MDX expressions. For example, to create a `Profit Margin` calculated measure:
CREATE MEMBER CURRENTCUBE.[Measures].[Profit Margin] AS
([Measures].[Sales Amount] - [Measures].[Cost Amount]) / [Measures].[Sales Amount],
FORMAT_STRING = "Percent"
Measures in the User Interface
In SQL Server Data Tools (SSDT) or Visual Studio with the Analysis Services projects extension, measures are configured within the dimension and cube designers. You can define new measures, modify existing ones, and set their properties.
Important Consideration: The choice of aggregation function is critical. An incorrect aggregation can lead to misleading analytical results. Always ensure the aggregation matches the business meaning of the measure.
Best Practices for Measures
- Meaningful Names: Use clear and descriptive names for all measures.
- Consistent Aggregations: Apply consistent aggregation functions to similar measures.
- Use Format Strings: Apply appropriate format strings for better presentation.
- Leverage Calculated Measures: Use calculated measures for derived business logic.
- Organize into Measure Groups: Keep related measures together for better model organization.
Understanding and effectively utilizing measures is fundamental to building robust and insightful multidimensional data models in SQL Server Analysis Services.