Predictive Analytics Using Rattle and Qlik Sense

Create comprehensive solutions for predictive analysis using Rattle and share them with Qlik Sense
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Predictive Analytics Using Rattle and Qlik Sense

Ferran Garcia Pagans

3 customer reviews
Create comprehensive solutions for predictive analysis using Rattle and share them with Qlik Sense
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Book Details

ISBN 139781784395803
Paperback242 pages

Book Description

Qlik Sense Desktop, the personal and free version of Qlik Sense, is a powerful tool for business analysts to analyze data and create useful data applications. Rattle, developed in R, is a GUI used for data mining and complements Qlik Sense Desktop very well. By combining Rattle and Qlik Sense Desktop, a business user can learn how to apply predictive analytics to create real-world data applications. The objective is to use Qlik Sense to analyze data and complement it with predictive analytics using Rattle.

This book will introduce you to basic predictive analysis techniques using Rattle and basic data visualizations concepts using Qlik Sense Desktop. You will start by setting up Qlik Sense Desktop, R, and Rattle and learn the basic of these tools. Then this book will examine the data and make it ready to be analyzed. After that, you will get to know the key concepts of predictive analytics, by building simple models with Rattle and creating visualizations with Qlik Sense Desktop. Finally, the book will show you the basics of data visualization and will help you to create your first data application and dashboard.

Table of Contents

Chapter 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 Rattle
Installing Qlik Sense Desktop
Exploring Qlik Sense Desktop
Further learning
Summary
Chapter 2: Preparing Your Data
Datasets, observations, and variables
Loading data
Transforming data
Cleaning up
Exporting data
Further learning
Summary
Chapter 3: Exploring and Understanding Your Data
Text summaries
Visualizing distributions
Correlations among input variables
Further learning
Summary
Chapter 4: Creating Your First Qlik Sense Application
Customer segmentation and customer buying behavior
Loading data and creating a data model
Creating a simple data app
Associative logic
Creating charts
Analyzing your data
Further learning
Summary
Chapter 5: Clustering and Other Unsupervised Learning Methods
Machine learning – unsupervised and supervised learning
Further learning
Summary
Chapter 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
Ensemble classifiers
Other models
Further learning
Summary
Chapter 7: Model Evaluation
Cross-validation
Regression performance
Measuring the performance of classifiers
Further learning
Summary
Chapter 8: Visualizations, Data Applications, Dashboards, and Data Storytelling
Data visualization in Qlik Sense
Data analysis, data applications, and dashboards
Data storytelling with Qlik Sense
Further learning
Summary
Chapter 9: Developing a Complete Application
Understanding the bike rental problem
Exploring the data with Qlik Sense
Creating a Qlik Sense App to control the activity
Using Rattle to forecast the demand
Model evaluation
Further learning
Summary

What You Will Learn

  • Set up your desktop environment by installing Qlik Sense Desktop, R, and Rattle
  • Explore Rattle charts and the most commonly used multivariate statistical techniques to discover relationships among data
  • Find solutions to business questions by applying data analysis techniques
  • Use unsupervised and supervised learning methods to gain insights into your data
  • Evaluate the performance of a predictive model
  • Create basic charts and filters using Qlik Sense Desktop to build your first data application
  • Improve your analysis by complementing Qlik Sense Desktop with predictive analytics
  • Familiarize yourself with the basics of data visualization and data storytelling

Authors

Table of Contents

Chapter 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 Rattle
Installing Qlik Sense Desktop
Exploring Qlik Sense Desktop
Further learning
Summary
Chapter 2: Preparing Your Data
Datasets, observations, and variables
Loading data
Transforming data
Cleaning up
Exporting data
Further learning
Summary
Chapter 3: Exploring and Understanding Your Data
Text summaries
Visualizing distributions
Correlations among input variables
Further learning
Summary
Chapter 4: Creating Your First Qlik Sense Application
Customer segmentation and customer buying behavior
Loading data and creating a data model
Creating a simple data app
Associative logic
Creating charts
Analyzing your data
Further learning
Summary
Chapter 5: Clustering and Other Unsupervised Learning Methods
Machine learning – unsupervised and supervised learning
Further learning
Summary
Chapter 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
Ensemble classifiers
Other models
Further learning
Summary
Chapter 7: Model Evaluation
Cross-validation
Regression performance
Measuring the performance of classifiers
Further learning
Summary
Chapter 8: Visualizations, Data Applications, Dashboards, and Data Storytelling
Data visualization in Qlik Sense
Data analysis, data applications, and dashboards
Data storytelling with Qlik Sense
Further learning
Summary
Chapter 9: Developing a Complete Application
Understanding the bike rental problem
Exploring the data with Qlik Sense
Creating a Qlik Sense App to control the activity
Using Rattle to forecast the demand
Model evaluation
Further learning
Summary

Book Details

ISBN 139781784395803
Paperback242 pages
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From 3 reviews

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