Data Mining with SQL Server 2012

BI-DMNNG12-401-EN

Acquire in-depth knowledge about the business questions data mining can answer and the processes involved in data mining projects. Explore and understand your data and data mining algorithms to create data mining models and evaluate them.

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Duration: 24 hours

Level: 400

Objectives

  • Describe what data mining is and what business questions it can 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 2012 Integration Services data mining tasks
  • Do text mining with Integration Services and with Full-Text and Semantic Search
  • 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 2008 Reporting Services

”Several members of the class were impressed that he could answer any question without having to consult reference material”

WHEN and WHERE is this course running?

What does this course cover?

The Data Mining course was developed in-house by SolidQ. In it you will learn how to use data mining to find advanced patterns in their data, and perform predictions based on the patterns found using SQL Server 2012 Analysis Services. The Data Mining course is a high-end course, enabling you to go beyond simple usage of wizards. In-depth understanding of the data mining algorithms, how they are built and how they work, is provided.

Who is this course designed for?

  • Business intelligence application developers
  • Advanced database administrators
  • Advanced analysts

 

Pre-requisites: What do you need to know?

  • At least moderate experience with data warehousing, reporting and On-Line Analytical Processing
  • Familiarity with the Transact-SQL language
  • Knowledge of a .NET language like C# or VB.NET is welcome as well

All our courses can be offered as a private delivery and tailored for your team's specific needs

Contact us

Course outline

Module 01: Introduction to Data Mining
  • Introduction to Data Mining
  • Business Questions
  • Data Mining Process
  • SQL Server Data Mining Tools

Lab 01: Using SSMS and SSDT to Explore Sample Databases and a Sample Project

Module 02: Understanding the Data
  • Cases, Variables, and Measures
  • Descriptive Statistics with T-SQL and CLR
  • Data Profiling with SSIS, SSAS and SSRS
  • Measuring Information

Lab 02: Using an SSAS Multidimensional Cube and Excel to Get a Data Overview

Module 03: Data Preparation
  • Missing Values and Outliers
  • Derived Variables
  • Time Series
  • Sampling and Testing the Sampling

Lab 03: Using SSIS to Split the Data into Training and Test Set and Checking the Split with Decision Trees

Module 04: Data Mining Algorithms, Part 1
  • Naïve Bayes
  • Decision Trees
  • Linear Regression and Regression Trees

Lab 04: Using the Naïve Bayes and Decision Trees Algorithms

Module 05: Data Mining Algorithms, Part 2
  • Neural Network and Logistic Regression
  • Predictive Models Evaluation
  • Time Series

Lab 05: Using the Neural Network and Time Series Algorithms, and Evaluating Predictive Models

Module 06: Data Mining Algorithms, Part 3
  • Association Rules
  • Clustering
  • Sequence Clustering

Lab 06: Using the Association Rules, Clustering, and Sequence Clustering Algorithms

Module 07: Data Mining Extensions (DMX) Language
  • XMLA and Data Mining Objects
  • DDL Statements
  • DML Statements
  • DMX Select Statement

Lab 07: Using the DMX Language

Module 08: Integration with SQL Server BI Suite
  • Integration with SSIS
  • Integration with SSRS
  • Integration with SSAS

Lab 08: Integrating Data Mining with SSIS, SSRS, and SSAS

Module 09: Data Mining with Excel
  • Excel Data Preparation and Data Mining
  • Table Analysis with Excel
  • Combining Data Mining with PowerPivot

Lab 09: Using the Data Mining Client for Excel for Data Preparation and Analysis

Module 10: Analyzing Texts
  • Text Mining with SSIS
  • Using Full-Text Search (FTS)
  • Using Semantic Search (SS)

Lab 10: Text Mining with SSIS

Module 11: Developing Data Mining Applications
  • Advanced DMX
  • Developing Data Mining Models with AMO
  • Using ADOMD.NET Client
  • Server Procedures and ADOMD.NET Server Components

Lab 11: Using Advanced DMX

Module 12: Administering Data Mining Models
  • Managing SSAS Databases
  • Monitoring SSAS
  • Data Mining Security

Lab 12: Securing, Backing Up, and Processing Data Mining Models

WHEN and WHERE is this course running next?

This course may be scheduled in more than one region. Please check availability in your country.

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