Microsoft Analysis Services & Excel PowerPivot

Full Course Name:
Data Mining, Predictive Analytics with Microsoft Analysis Services and Excel PowerPivot

This three-day instructor-led course will introduce the students to the concepts of data mining, machine learning and predictive analytics utilizing the Microsoft toolsets including SQL Server Analysis Services and Excel with PowerPivot and the Data Mining Add-ins.

Audience
This course is intended for Power Users, IT Professionals, Report Developers, BI Professionals, Project Managers and Team Leads interested in exploring the Microsoft toolsets for data mining, machine learning, and predictive analytics.

At Course Completion
After completing this course, students will be able to:
•     Have a firm understanding of the concept of data mining.
•     Explore the user interface.
•     Use offline mode and immediate mode.
•     Create and configure a data source.
•     Create and configure data view.
•     Explore data.
•     Create and configure named calculation.
•     Create and configure named queries.
•     Walk-through a project to completion.
•     Explore the models.
•     Compare mining structures.
•     Use cross validation.
•     Create reports using Reporting Services.
•     Save queries.
•     Save results to the database.
•     Create multiple nested tables off of a case table.
•     Use Microsoft Association Rules Algorithm.
•     Use Microsoft Sequence Clustering Algorithm.
•     Use Microsoft Time Series Algorithm.
•     Use Microsoft Neural Network Algorithm.
•     Properly prepare data for mining.
•     Use Model Usage—Browse.
•     Use Model Usage—Query.
•     Use Accuracy and Validation.
•     Use Decision Trees.
•     Use Logistic Regression.
•     Use Nave Bayes.
•     Use Neural Network.
•     Use Estimate Tool.
•     Use Cluster.
•     Use Associate Tool.
•     Use Forecast Tool.
•     Use Table Analysis Tools.
•     Use Visio Add-In.
•     Complete five different business scenarios that further reinforce the concepts learned.

Prerequisites
Before attending this course, students must have:
•     Experience with Excel
•     Basic understanding of business analytics