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Predictive Analytics Using Rattle and Qlik Sense

You're reading from  Predictive Analytics Using Rattle and Qlik Sense

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781784395803
Pages 242 pages
Edition 1st Edition
Languages
Authors (2):
Ferran Garcia Pagans Ferran Garcia Pagans
Profile icon Ferran Garcia Pagans
Fernando G Pagans Fernando G Pagans
Profile icon Fernando G Pagans
View More author details
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Table of Contents (16) Chapters close

Predictive Analytics Using Rattle and Qlik Sense
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Ready with Predictive Analytics 2. Preparing Your Data 3. Exploring and Understanding Your Data 4. Creating Your First Qlik Sense Application 5. Clustering and Other Unsupervised Learning Methods 6. Decision Trees and Other Supervised Learning Methods 7. Model Evaluation 8. Visualizations, Data Applications, Dashboards, and Data Storytelling 9. Developing a Complete Application Index

Introducing R, Rattle, and Qlik Sense Desktop


In this section, we will introduce the tools we'll use in this book: R, Rattle, and Qlik Sense Desktop.

R is a free programming language for statistics and graphics available under the terms of the Free Software Foundation's General Public License (GNU). The R language is widely accepted for statistical analysis and data mining. There is a big community of developers that develop new packages for R, such as Rattle.

R is a very powerful and flexible programming language, but to create predictive models with R you need to be a skilled programmer. For this reason, we will use Rattle.

Rattle is a Graphical User Interface (GUI) for data mining developed by Graham Williamson using R. Similar to R, Rattle is also licensed under the GNU. R and Rattle are the predictive analysis environments that we will be using in this book.

Using Rattle, we'll be able to load and prepare data, create a predictive model, and evaluate its performance without writing R code; Rattle will write the code for us.

In order to create a visual and intuitive application for the business user, we'll use Qlik Sense Desktop, the personal and free version of Qlik Sense. Qlik Sense is a self-service data visualization tool developed by Qlik.

We'll use Qlik Sense Desktop instead of Qlik Sense Enterprise because we want to build a free learning environment to develop the examples of this book. For the propose of this book, Qlik Sense Desktop and Qlik Sense are very similar. When you deploy your applications in Qlik Sense Enterprise, the platform provides you:

  • Data governance.

  • Security

  • Scalability

  • High availability

Qlik has two different tools for data analysis and data visualization: QlikView and Qlik Sense. Each tool is designed to solve a different problem:

  • With QlikView, developers have a powerful tool to create guided analytic applications

  • With Qlik Sense, business users can create their own analysis and visualizations with drag and drop simplicity

We will use Qlik Sense Desktop instead of QlikView because the book is written for business users and analysts, and Qlik Sense is designed to provide business users with the ability to create visualizations on their data.

  • Qlik Sense has two different editions:

  • Qlik Sense Enterprise, a sever based edition for use in organizations.

  • Qlik Sense Desktop, a desktop edition for personal use.

  • In this book we’ll use Qlik Sense Desktop to complete the examples. This edition is free for personal utilization.

R and Rattle can be installed on Windows, Mac OS, and Linux, but Qlik Sense Desktop can only be installed on a Windows machine. For this reason, we will use a Windows-based computer for this book. Qlik Sense Desktop and R load all data into memory; we suggest that you use a 64-bit computer instead of a 32-bit computer.

In order to install R, Rattle, and Qlik Sense Desktop, you'll need administration rights, and an Internet connection to download the software.

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Predictive Analytics Using Rattle and Qlik Sense
Published in: Jun 2015 Publisher: ISBN-13: 9781784395803
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