Data Mining Extensions (DMX)

Introduction to Data Mining Extensions (DMX)

Data Mining Extensions (DMX) is a proprietary query language developed by Microsoft for Microsoft SQL Server Analysis Services (SSAS). DMX is used to create, query, and manage data mining models. It provides a powerful and flexible way to interact with the data mining capabilities within SSAS.

What is DMX?

DMX is designed to work with the multidimensional data structures that are common in data warehousing and business intelligence. It allows users to:

Query mining models to retrieve predictions, associated items, cluster centroids, and other mining results.
Create new mining models using various algorithms supported by SSAS.
Modify existing mining models.
Work with stored procedures and functions related to data mining.

Key DMX Concepts

DMX queries typically involve these core components:

SELECT Statement: Used to query data mining models. This is similar to SQL's SELECT statement but adapted for mining model structures.
FROM Clause: Specifies the mining model to be queried or the data source for creating a model.
WHERE Clause: Filters the data used for querying or training.
PREDICTION JOIN: A crucial DMX clause used to join predicted results from a mining model back to source data.
Data Mining Algorithms: DMX supports various algorithms like:
- Association Rules
- Clustering
- Classification (Decision Trees, Naive Bayes, Logistic Regression)
- Forecasting
- Sequence Clustering
- Linear Regression

Example DMX Query (Predicting a Purchase)

Here's a simple example of a DMX query to predict whether a customer will purchase a specific product, based on an existing mining model:


SELECT
    [Customer].[CustomerID],
    [Product].[ProductID],
    [Purchase Prediction] AS [Will Purchase]
FROM
    [Customer Purchase Model].PROFILE(
        NEW HIERARCHY_HINT(
            [Product].[ProductID] = 321,
            [Customer].[CustomerID] = 789
        )
    )
WHERE
    [Purchase Prediction] = 1

DMX vs. MDX

It's important to distinguish DMX from Multidimensional Expressions (MDX). While both are query languages for SQL Server Analysis Services, they serve different purposes:

DMX: Used for data mining models, querying predictions, and creating models.
MDX: Used for querying multidimensional cubes (OLAP data), navigating hierarchical structures, and performing aggregations.

Getting Started with DMX

To start working with DMX, you typically need:

SQL Server Analysis Services installed.
A data mining project within a SQL Server Analysis Services instance.
A trained data mining model.
Tools like SQL Server Management Studio (SSMS) or Visual Studio with Analysis Services projects.