Data Mining - Using MS Excel

Details

Services

• Lunch / Catering
• Assistance for hotel / travel bookings
• Comelio certificate
• Flexible: Free cancellation up until one day before the training

Summary

Microsoft SQL Server Business Intelligence delivers a comprehensive platform empowering organizations to build and deploy secure, scalable, and manageable BI solutions. The Data Mining module provides new business insights, a reliable basis for forecasting and a comprehensive data-mining development environment. The Data Mining Add-ins allow you to harness the power of SQL Server predictive analytics in Excel and Visio. Use Table Analysis Tools to get insight with a couple of clicks. Use the Data Mining tab for full-lifecycle data mining, and build models which can be exported to a production server. Visualize your models in Visio. Microsoft SQL Server Analysis Services provides multiple algorithms for use in your data mining solutions. These algorithms are implementations of some of the most popular methodologies used in data mining. This training covers both the functions of the Data Mining Add-ins and the functions of SQL Server Data Tools. While getting to know the various software modules you will also get familiar with algorithms like Decision Trees, Naive Bayes, Clustering, Neural Networks, or Linear and Logistic Regression.

Agenda

Data Mining and MS SQL Server - Introduction

Business Intelligence and Data Mining - Usage Scenarios for Data Mining - Data Mining Techniques in Microsoft SQL Server and MS Excel - Server and Client Components: MS SQL Server Analysis Services and Data Mining Add-Ins for MS Excel and MS Visio - Data Mining Life Cycle and Tasks - Data Mining Techniques in MS SQL Server - Project Cycle (Data Collection, Processing and Cleaning of Data, Modeling, Model Evaluation, Reporting, Forecasting, Integration into Applications, Model Management and Maintenance)

Classification using Microsoft Decision Trees

Introduction to the Algorithm - Parameters - Building a Model and Using the Model - DMX Queries - Classification Model, Regression Model, Relationship Model

Classification using Microsoft Naive Bayes

Introduction to the Algorithm - Parameters - Building a Model and Using the Model - DMX Queries - Dependency Network, Attribute Profiles, Attribute Characteristics, Attribute Discrimination

Microsoft Time Series

Introduction to the Algorithm - Parameters - Building a Model and Using the Model: Auto Regression, Multiple Time Series, Seasonality, Historic Predictions, Caching Predictions - DMX Queries

Microsoft Clustering

Introduction to the Algorithm - Parameters - Building a Model and Using the Model: Clustering Types, Scalable Clustering, Predictions and Cluster Assignment - DMX Queries: Cluster, Probability, Histograms, CaseLikelihood

Microsoft Sequence Clustering

Introduction to the Algorithm - Parameters - Building a Model and Using the Model: Markov Chains, Transition Matrix, Clustering and Markov Chains, Decomposition - DMX Queries

Microsoft Association Rules

Introduction to the Algorithm - Parameters - Building a Model and Using the Model: Itemset, Support, Probability and Confidence, Interestingness and Importance - DMX Queries

Microsoft Neural Network

Introduction to the Algorithm - Parameters - Building a Model and Using the Model: Combination and Activation, Normalization and Mapping, Topology of a Neural Network , Model Training - DMX Queries

Table Analysis Tools for Excel

Data Cleaning and Sampling - Prediction Calculator - Shopping Basket Analysis

Data Mining Client for Excel

Adding and Processing Structures and Models - Testing Models - Data Mining Queries - Using Data Mining-Models in Integration Services – Using Data Mining Results in Reporting Services