55040 Data Mining, Predictive Analytics with Microsoft Analysis Services and Excel PowerPivot

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Overview

This 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.

Objectives

  • 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 Naïve 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.

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.

Syllabus

Introduction

  • Introduction
  • Course Materials
  • Facilities
  • Prerequisites
  • What We'll Be Discussing

Data Mining Concepts

  • Concepts and Terminology
  • Data Mining and Results
  • CRISP-DM
  • Business Problems for Data Mining
  • Models, Induction, and Prediction
  • Data Mining Tasks
  • Key Concepts
  • Lab 1: Data Mining Concepts

SQL Server Analysis Services Data Mining Tools

  • Introduction to SQL Server Data Tools
  • Project Walk-Through
  • Stepping Through the Data Mining Wizard
  • Testing and Validation of Mining Models
  • Cross Validation
  • The Mining Model Prediction Tab
  • Reports
  • Lab 1: SQL Server Analysis Services Data Mining Tools

The Microsoft Data Mining Algorithms

  • Types of Data Mining Algorithms
  • Microsoft Decision Trees Algorithm
  • Microsoft Linear Regression Algorithm
  • Microsoft Clustering Algorithm
  • Microsoft Naïve Bayes Algorithm
  • Microsoft Association Algorithm
  • Microsoft Sequence Clustering Algorithm
  • Microsoft Time Series Algorithm
  • Microsoft Neural Network Algorithm
  • Microsoft Logistic Regression Algorithm
  • Lab 1: The Microsoft Data Mining Algorithms

Excel PowerPivot Data Mining Add-ins

  • Data Mining Tab
  • Connection
  • Data Preparation
  • Management
  • Model Usage
  • Accuracy and Validation
  • Data Modeling
  • Visio Data Mining Add-In
  • Lab 1: Excel PowerPivot Data Mining Add-ins

Concept Reinforcement Scenarios

  • Scenario 1
  • Scenario 2
  • Scenario 3
  • Scenario 4
  • Scenario 5
  • Lab 1: Concept Reinforcement Scenarios

Training provider

Teaching mode:
Classroom - Instructor Led
Online - Instructor Led
Duration: 3 days
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Our pricing

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