Predictive Analytics Using Rattle and Qlik Sense

By Ferran Garcia Pagans

About This Book

• Create visualizations, dashboards, and data applications with Qlik Sense and Rattle
• Load, explore, and manipulate data to Rattle to create predictions and discover hidden patterns in the data
• A step-by-step guide to learning predictive analytics in a quick and easy way

Who This Book Is For

If you are a business analyst who wants to understand how to improve your data analysis and how to apply predictive analytics, then this book is ideal for you. This book assumes you have some basic knowledge of statistics and a spreadsheet editor such as Excel, but knowledge of QlikView is not required.

• Language: English
• Publisher: Packt Publishing
• Release date: Jun 30, 2015
• ISBN: 9781784390785

Book preview

Table of Contents

Predictive Analytics Using Rattle and Qlik Sense

Credits

About the Author

About the Reviewers

www.PacktPub.com

Support files, eBooks, discount offers, and more

Why subscribe?

Free access for Packt account holders

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Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. Getting Ready with Predictive Analytics

Analytics, predictive analytics, and data visualization

Purpose of the book

Introducing R, Rattle, and Qlik Sense Desktop

Installing the environment

Downloading and installing R

Starting the R Console to test your R installation

Downloading and installing Rattle

Installing Qlik Sense Desktop

Exploring Qlik Sense Desktop

Further learning

Summary

2. Preparing Your Data

Datasets, observations, and variables

Loading data

Loading a CSV File

Transforming data

Transforming data with Rattle

Rescaling data

Using the Impute option to deal with missing values

Recoding variables

Binning

Indicator variables

Join Categories

As Category

As Numeric

Cleaning up

Exporting data

Further learning

Summary

3. Exploring and Understanding Your Data

Text summaries

Summary reports

Measures of central tendency – mean, median, and mode

Measures of dispersion – range, quartiles, variance, and standard deviation

Range

Quartiles

Variance

Standard deviation

Measures of the shape of the distribution – skewness and kurtosis

Showing missing values

Visualizing distributions

Numeric variables

Box plots

Histograms

Cumulative plots

Categorical variables

Bar plots

Mosaic plots

Correlations among input variables

The Explore Missing and Hierarchical options

Further learning

Summary

4. Creating Your First Qlik Sense Application

Customer segmentation and customer buying behavior

Loading data and creating a data model

Preparing the data

Creating a simple data app

Associative logic

Creating charts

Analyzing your data

Further learning

Summary

5. Clustering and Other Unsupervised Learning Methods

Machine learning – unsupervised and supervised learning

Cluster analysis

Centroid-based clustering the using K-means algorithm

Customer segmentation with K-means clustering

Preparing the data in Qlik Sense

Creating a customer segmentation sheet in Qlik Sense

Hierarchical clustering

Association analysis

Further learning

Summary

6. Decision Trees and Other Supervised Learning Methods

Partitioning datasets and model optimization

Decision Tree Learning

Entropy and information gain

Underfitting and overfitting

Using a Decision Tree to classify credit risks

Using Rattle to score new loan applications

Creating a Qlik Sense application to predict credit risks

Ensemble classifiers

Boosting

Random Forest

Supported Vector Machines

Other models

Linear and Logistic Regression

Neural Networks

Further learning

Summary

7. Model Evaluation

Cross-validation

Regression performance

Predicted versus Observed Plot

Measuring the performance of classifiers

Confusion matrix, accuracy, sensitivity, and specificity

Risk Chart

ROC Curve

Further learning

Summary

8. Visualizations, Data Applications, Dashboards, and Data Storytelling

Data visualization in Qlik Sense

Visualization toolbox

Creating a bar chart

The Data menu

The Sorting menu

The Add-ons menu

The Appearance menu

Data analysis, data applications, and dashboards

Qlik Sense data analysis

In-memory analysis

Associative experience

Data applications and dashboards

The DAR approach

Data storytelling with Qlik Sense

Creating a new story

Further learning

Summary

9. Developing a Complete Application

Understanding the bike rental problem

Exploring the data with Qlik Sense

Checking for temporal patterns

Visual correlation analysis

Creating a Qlik Sense App to control the activity

Using Rattle to forecast the demand

Correlation Analysis with Rattle

Building a model

Improving performance

Model evaluation

Scoring new data

Further learning

Summary

Index

Predictive Analytics Using Rattle and Qlik Sense

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Predictive Analytics Using Rattle and Qlik Sense

Copyright © 2015 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: June 2015

Production reference: 1260615

Published by Packt Publishing Ltd.

Livery Place

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Birmingham B3 2PB, UK.

ISBN 978-1-78439-580-3

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Credits

Author

Ferran Garcia Pagans

Reviewers

Gert Jan Feick

Miguel Ángel García

Commissioning Editor

Dipika Gaonkar

Acquisition Editor

Reshma Raman

Content Development Editor

Ajinkya Paranjape

Technical Editor

Narsimha Pai

Copy Editors

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Kevin McGowan

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Project Coordinator

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Proofreader

Safis Editing

Indexer

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Graphics

Sheetal Aute

Production Coordinator

Komal Ramchandani

Cover Work

Komal Ramchandani

About the Author

Ferran Garcia Pagans studied software engineering at the University of Girona and Ramon Llull University. After that, he did his masters in business administration at ESADE Business School. He has 16 years of experience in the software industry, where he helped customers from different industries to create software solutions. He started his career working at the Ramon Llull University as a teacher and researcher. Then, he moved to the Volkswagen group as a software developer. After that, he worked with Oracle as a Java, SOA, and BPM specialist. Currently, he is a solution architect at Qlik, where he helps customers to achieve competitive advantages with data applications.

I would like to thank my love, Laura.

About the Reviewers

Gert Jan Feick studied informatics (language, knowledge, and interaction) at Technical University Enschede (NL). He started his career as a project manager at a medium-sized software development company, specializing in requirement analysis and project management. From 2005 onward, he was responsible for building up a company in the areas of software development, reporting and visualizations, and analysis. In 2011, he moved to Germany and became a management consultant at Infomotion GmbH, where he was responsible for the team that works on self-service and Agile BI as well as reporting and analysis.

He regularly contributes to online forums (including the Qlik Community), speaks at conventions, and writes articles. You can follow him on Twitter at @gjfeick, where he tweets about QlikView, big data, self-service and Agile BI, data visualization, and other topics in general.

Miguel Ángel García is a Business Intelligence consultant and QlikView Solutions Architect. Having worked throughout many successful QlikView implementations, from inception through implementation, and performed across a wide variety of roles on each project; his experience and skills range from presales to applications development and design, technical architecture, system administration, functional analysis, and overall project execution.

He is the co-author of QlikView 11 for Developers, Packt Publishing, which was published in November 2012, and its corresponding translation into Spanish QlikView 11 para Desarrolladores, published in December 2013. He also worked as a technical reviewer for several other QlikView books.

He runs a QlikView consultancy, AfterSync (www.aftersync.com), through which he helps customers discover the power of the Qlik platform.

He currently holds the QlikView Designer, QlikView Developer, and QlikView System Administrator certifications, issued by Qlik, for Versions 9, 10, and 11.

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Preface

Today, a lot of organizations are investing in improving their analytics skills and tools. They know that, by analyzing their data, they can improve the performance of their business process and achieve real value from that.

The objective of this book is to introduce you to predictive analytics and data visualization by developing some example applications. We'll use R and Rattle to create the predictive model and Qlik Sense to create a data application that allows business users to explore their data.

We use Rattle and Qlik Sense to avoid learn programming and focus on predictive analytics and data visualizations concepts.

What this book covers

Chapter 1, Getting Ready with Predictive Analytics, explains the key concepts of predictive analytics and how to install our learning environments, such as Qlik Sense, R, and Rattle.

Chapter 2, Preparing Your Data, covers the basic characteristics of datasets, how to load a dataset into Rattle, and how to transform it. As data is the basic ingredient of analytics, preparing the data to analyze it is the first step.

Chapter 3, Exploring and Understanding Your Data, introduces you to Exploratory Data Analysis (EDA) using Rattle. EDA is a statistical approach to understanding data.

Chapter 4, Creating Your First Qlik Sense Application, discusses how to load a dataset into Qlik Sense, create a data model and basic charts, and explore data using Qlik Sense. Using Exploratory Data Analysis and Rattle to understand our data is a very mathematical approach. Usually, business users prefer a more intuitive approach, such as Qlik Sense

Chapter 5, Clustering and Other Unsupervised Learning Methods, covers machine, supervised, and unsupervised learning but focuses on unsupervised learning We create an example application using K-means, a classic machine learning algorithm. We use Rattle to process the dataset and then we load it into Qlik Sense to present the data to the business user.

Chapter 6, Decision Trees and Other Supervised Learning Methods, focuses on supervised learning. It helps you create an example application using Decision Tree Learning. We use Rattle to process the data and Qlik Sense to communicate with it.

Chapter 7, Model Evaluation, explains how to evaluate the performance of a model. Model evaluation is very useful to improve the performance.

Chapter 8, Visualizations, Data Applications, Dashboards, and Data Storytelling, focuses on data visualization and data storytelling using Qlik Sense.

Chapter 9, Developing a Complete Application, explains how to create a complete application. It covers how to explore the data, create a predictive model, and create a data application.

What you need for this book

To install our learning environment and complete the examples, you need a 64-bit computer:

OS: Windows 7, Windows 8, or 8.1

Processor: Intel Core2 Duo or higher

Memory: 4 GB or more

.NET Framework: 4.0

Security: Local admin privileges to install R, Rattle, and Qlik Sense.

Who this book is for

If you are a business analyst who wants to understand how to improve your data analysis and how to apply predictive analytics, then this book is ideal for you. This book assumes that you to have some basic knowledge of QlikView, but no knowledge of implementing predictive analysis with QlikView. It would also be helpful to be familiar with the basic concepts of statistics and a spreadsheet editor, such as Excel.

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: After you have downloaded it, type library(rattle) and R will load the Rattle package into memory, and you will be able to use it.

A block of code is set as follows:

If Purpose = 'Education' AND Sex = 'male' AND Age > 25 Then No Default

If Purpose = 'Education' AND Sex = 'male' AND Age < 25 Then Yes Default

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: Don't be afraid, we will use two software tools Rattle and Qlik Sense Desktop in order to avoid complex code.

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

Reader feedback

Feedback from our readers is always welcome. Let us know what you think about this book—what you liked or disliked. Reader feedback is important for us as it helps us develop titles that you will really get the most out of.

To send us general feedback, simply e-mail <[e-mail]>, and mention the book's title in the subject of your message.

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Downloading the example code

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