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.