Data Mining, Data Mining Learning, Data Mining Training, Data Mining SQL, Data Mining SQL Server 2005 - Course

Data Mining with SQL Server 2005

Choose your own date

3-Day (BI-DMNNG05-401-EN)

Description
Audience
Prerequisites
Course Objectives

Description

In this course attendees learn how to use Data Mining to find advanced patterns in their data and perform predictions based on the patterns found using SQL Server 2005 Analysis Services.

Audience

This course is intended for business intelligence application developers and advanced administrators.

Prerequisites

The attendees should have at least moderate experience with data warehousing, reporting and On-Line Analytical Processing. The attendees should be familiar with the Transact-SQL language. Knowledge of a .NET language like C# or VB.NET is welcome as well.

Course Objectives

On course completion you will be able to:

Describe what Data Mining is and what business questions can it answer

Explain the process of a Data Mining project

Explore and understand your data using descriptive statistics, OLAP cubes, reports and other tools

Prepare the data to make better models

Understand the Data Mining algorithms, and when to use them

Create Data mining Models and browse them

Evaluate models to find the one that gives best results

Use SQL Server 2005 Integration Services Data Mining tasks

Do Text Mining with Integration Services

Understand and use the Data Mining Extensions (DMX) language

Deploy Data Mining models in production using custom application, OLAP cubes or reports developed with SQL Server 2005 Reporting Services

Content

Module 1: Introduction to Data Mining IntroductionBusiness Questions Process Tools

Module 2: Understanding and Preparing the data Using OLAP cubes and reports Derived variables Missing values and outliers Descriptive statistics Information theory Sampling and confidence

Module 3: Data Mining Algorithms Part 1 Naïve Bayes
Decision Trees
Neural Networks
Linear Regression
Logistic Regression

Module 4: Data Mining Algorithms Part 2 Clustering Sequence Clustering Association Rules Time Series

Module 5: Using Integration Services with Data Mining Data Mining tasks Data Mining transforms Data Mining preparation Text Mining

Module 6: DMX Language DDL statements DML statement DMX Select Advanced examples

Module 7: Integrating Data Mining in BI applicationsPreparing Data Mining reports with Reporting Services Integrating with OLAP cubes

Module 8: Developing Data Mining Applications XMLA Developing models with AMO Building intelligent applications using ADOMD.NET Client Client browsers Server stored procedures with ADOMD.NET Server

Module 9: Managing and Maintaining Data Mining modelsDeployment Backing up and restoring Security

Course MaterialsPrinted student manual (in English) Student CD with exercises, labs and supporting materials

The following software is used during the workshop:

MS SQL Server 2005 Developer Edition
MS Visual Studio .NET 2005 Professional