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SSAS 2012, Part 10: Data Mining

with expert Thomas LeBlanc

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SSAS 2012, Part 10: Data Mining Trailer

Course at a glance

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Release date Release date 1/25/2013
Level Level Intermediate
Runtime Runtime 1h 31m
Platform Platform Major browsers on Windows Major browsers on Windows Major browsers on Mac OSX Major browsers on Mac OSX Mobile Devices Mobile Devices
Closed captioning Closed captioning N/A
Transcript Transcript N/A
eBooks / courseware eBooks / courseware N/A
Hands-on labs Hands-on labs N/A
Sample code Sample code N/A
Exams Exams Included

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Course description

Data Mining is an analytical process to explore data looking for patterns. In this course, you will learn how to create a model from a data source and by using data sets and SQL Server Data Tools analyze data. By using business questions like "what customers may be inclined to buy a product" or "how products are grouped" to looking for patterns of fraud, business analytics are a powerful tool to both examine data and look for predictions. Finally, when Data Mining should be used vs a Lift chart will explained giving you power choices in getting control of your data.


This course assumes that students have working experience with SQL Server; basic relational database concepts (e.g., tables, queries, and indexing); data transformation services.

Meet the expert

Thomas LeBlanc Using Microsoft SQL Server started for Thomas with a Laboratory Information System in version 6.5. The Analysis Service (also called SSAS) option in version 7 got him excited about Data Warehousing, but before he used a production version of SSAS, he became a Database Administrator for versions 6.5 through 2005 while working at a paper mill and home health agency. After writing reports as an application developer for 10 years, he rediscovered Online Analytical Processing (OLAP) implemented into Data Warehouses. Since 2009, he has become a speaker in the SQL Server community and a voice for Microsoft Business Intelligence (MSBI) for enterprises. His transition from Sr. DBA to a Business Intelligence Architect has been a great career path. Thomas has certifications MCP, MCDBA and MCITP in Database Administration and Business Intelligence.

Course outline

Data Mining

Data Mining Concepts (22:13)
  • Introduction (00:32)
  • Mining Concepts (02:02)
  • Terminology (01:13)
  • Business Questions (02:45)
  • DMX Language (01:14)
  • Other Algorithm (03:55)
  • Demo: Data Mining (04:50)
  • Demo: Mining Views (05:11)
  • Summary (00:26)
Creating a Model (32:51)
  • Introduction (00:39)
  • Create a Mining Structure (01:41)
  • Predict to Buy Product (00:55)
  • Look at Data (01:33)
  • Model to Use (01:08)
  • Demo: Create a Model (00:21)
  • Demo: Clusters (00:00)
  • Demo: Adding More Algorithms (00:00)
  • Other Cluster Views (00:00)
  • Review Cluster (00:00)
  • Add Mining Model (00:00)
  • Modify/Review a Model (00:00)
  • Demo: Data Mining Wizard Cont. (00:00)
  • Demo: Data Mining Wizard (25:48)
  • Summary (00:42)
Accuracy and Predicting (35:55)
  • Introduction (00:40)
  • Add Filters (01:09)
  • Accuracy Chart (17:24)
  • Demo: Filter (05:54)
  • Use Data to Predict (01:21)
  • New Data (00:54)
  • Plug Into Model (00:47)
  • Run and Analyze (01:27)
  • Demo: Predict Based on a Model (05:36)
  • Summary (00:39)