MDX Overview

Multidimensional Expressions (MDX) is a query language that is used to query multidimensional data stored in Microsoft SQL Server Analysis Services (SSAS) and other OLAP (Online Analytical Processing) databases. MDX is to multidimensional data what SQL is to relational data.

MDX is a powerful and expressive language that allows you to:

Retrieve data from cubes.
Perform complex calculations and aggregations.
Slice and dice data along different dimensions.
Write custom business logic and KPIs.

Key Concepts in MDX

Cubes

A cube is a multidimensional data structure that organizes data into measures and dimensions. Measures represent numerical data that can be aggregated (e.g., sales amount, quantity), while dimensions represent hierarchical categories used to slice and analyze the measures (e.g., Time, Geography, Product).

Dimensions and Hierarchies

Dimensions are fundamental to multidimensional analysis. They can be structured hierarchically. For example, a 'Time' dimension might have a hierarchy with levels like Year, Quarter, Month, and Day. MDX allows you to navigate these hierarchies to aggregate or drill down into data.

Members

Members are individual items within a dimension or hierarchy. For instance, '2023' would be a member of the 'Year' level in the 'Time' dimension. 'North America' could be a member of a 'Region' level in a 'Geography' dimension.

Tuples

A tuple is a set of members, one from each of one or more dimensions. It represents a unique point in the multidimensional data space. For example, `([Measures].[Sales Amount], [Time].[2023], [Geography].[North America])` is a tuple that identifies the sales amount for North America in the year 2023.

Sets

A set is an ordered collection of tuples. Sets are used extensively in MDX to define the data that will be returned by a query. For example, you might want to retrieve all months within the year 2023, which would form a set of tuples.

Basic MDX Query Structure

An MDX query typically consists of the following clauses:

SELECT: Specifies the axes of the query (rows, columns, slicers) and the members to be displayed.
FROM: Specifies the cube or cubes that the query will retrieve data from.
WHERE: Acts as a slicer, filtering the data without displaying it on the axes.

Example: A Simple MDX Query

This query retrieves the 'Sales Amount' for the year '2023' and displays the 'Products' on the rows.


SELECT
  {[Measures].[Sales Amount]} ON COLUMNS,
  [Product].[Category].[Category].Members ON ROWS
FROM [Adventure Works]
WHERE ([Time].[Year].[2023])

In this example:

`[Measures].[Sales Amount]` specifies the measure to display.
`[Product].[Category].[Category].Members` selects all members of the 'Category' level in the 'Product' dimension for the rows.
`[Adventure Works]` is the name of the cube.
`[Time].[Year].[2023]` is a member that filters the data for the year 2023.

Note: MDX syntax is case-insensitive, but it's a good practice to maintain consistent casing for readability.

Learning MDX

Mastering MDX is essential for anyone working with SQL Server Analysis Services. The language offers extensive capabilities for data analysis and reporting. We recommend exploring the MDX Syntax and MDX Functions sections for deeper dives into specific elements of the language.

Key Takeaway: MDX provides a robust way to query and analyze multidimensional data, enabling sophisticated business intelligence solutions.

For more detailed information on MDX syntax and functions, please refer to the following sections.

Next: MDX Syntax | Previous: Multidimensional Modeling Introduction