DMX Overview

This document provides a comprehensive overview of the Multidimensional Expressions (DMX) language used in SQL Server Analysis Services (SSAS). DMX is a powerful query and data manipulation language specifically designed for working with the multidimensional data structures created in Analysis Services, such as cubes.

What is DMX?

DMX (Data Mining Extensions) is a syntax extension to SQL that allows you to query and manipulate data stored in multidimensional data models. While it shares some similarities with SQL, DMX is tailored for the hierarchical and structured nature of OLAP cubes.

Key Concepts

  • Cubes: The fundamental multidimensional data structure in SSAS.
  • Dimensions: Hierarchical structures that provide context for measures (e.g., Time, Geography, Product).
  • Measures: Numerical values that are aggregated across dimensions (e.g., Sales Amount, Quantity Sold).
  • Hierarchies: Levels within a dimension that allow for drilling down or rolling up data.
  • Members: Individual items within a hierarchy (e.g., "2023" in the Year hierarchy, "New York" in the City hierarchy).

DMX Query Structure

A basic DMX query consists of a SELECT statement, similar to SQL, but adapted for multidimensional data. The primary goal is to retrieve data from a cube based on specified dimensions and measures.

Basic SELECT Statement

SELECT
    { [Measures].[Sales Amount].Members, [Measures].[Quantity Sold].Members } ON COLUMNS,
    { [Date].[Calendar Year].Members, [Product].[Category].Members } ON ROWS
FROM
    [Adventure Works]`

In this example:

  • [Measures].[Sales Amount].Members and [Measures].[Quantity Sold].Members specify the measures to be displayed as columns.
  • [Date].[Calendar Year].Members and [Product].[Category].Members specify the dimension members to be displayed as rows.
  • [Adventure Works] specifies the target cube.

Common DMX Operations

  • Selecting Data: Retrieving specific cells or ranges of data from a cube.
  • Filtering Data: Using WHERE clauses to filter data based on dimension members or measure values.
  • Performing Calculations: Creating calculated members or using built-in functions for complex aggregations and analysis.
  • Working with Hierarchies: Navigating through different levels of a hierarchy.
  • Data Mining Queries: DMX is also used for querying data mining models.

DMX vs. MDX

It's important to distinguish DMX from MDX (Multidimensional Expressions). While both are used with SSAS, MDX is primarily for querying OLAP cubes, whereas DMX was originally designed for data mining extensions but is now broadly used for both data mining and cube querying. For modern cube querying, MDX is generally preferred, but understanding DMX provides valuable insight into SSAS capabilities.

Resources