Book Image

Advanced Analytics with R and Tableau

By : Ruben Oliva Ramos, Jen Stirrup, Roberto Rösler
Book Image

Advanced Analytics with R and Tableau

By: Ruben Oliva Ramos, Jen Stirrup, Roberto Rösler

Overview of this book

Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for data viz-savvy users who want to move into analytics and data science in order to enhance their businesses by harnessing the analytical power of R and the stunning visualization capabilities of Tableau. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau. In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics. By the end of this book, you will get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples.

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Table of Contents (16 chapters)
Advanced Analytics with R and Tableau
Advanced Analytics with R and Tableau
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Customer Feedback
Customer Feedback
Preface
Preface
Free Chapter
1
Advanced Analytics with R and Tableau
Advanced Analytics with R and Tableau
Installing R for Windows
RStudio
Implementing the scripts for the book
Tableau and R connectivity using Rserve
Summary
2
The Power of R
The Power of R
Core essentials of R programming
Data structures in R
Data frames
Control structures in R
For loops and vectorization in R
Functions
Creating your own function
Making R run more efficiently in Tableau
Summary
3
A Methodology for Advanced Analytics Using Tableau and R
A Methodology for Advanced Analytics Using Tableau and R
Industry standard methodologies for analytics
CRISP-DM
Team Data Science Process
Working with dirty data
Introduction to dplyr
Summary
4
Prediction with R and Tableau Using Regression
Prediction with R and Tableau Using Regression
Getting started with regression
Comparing actual values with predicted results
Getting started with multiple regression?
Solving the business question
Sharing our data analysis using Tableau
Summary
5
Classifying Data with Tableau
Classifying Data with Tableau
Business understanding
Understanding the data
Modeling in R
Model deployment
Decision trees in Tableau using R
Bayesian methods
Graphs
Summary
6
Advanced Analytics Using Clustering
Advanced Analytics Using Clustering
What is Clustering?
Finding clusters in data
Clustering in Tableau
Clustering example in Tableau
Interpreting your results
How Clustering Works in Tableau
Scaling
Clustering without using k-means
Statistics for Clustering
Introduction to R
Summary
7
Advanced Analytics with Unsupervised Learning
Advanced Analytics with Unsupervised Learning
What are neural networks?
Backpropagation and Feedforward neural networks
Evaluating a neural network model
Neural network performance measures
Visualizing neural network results
Neural network in R
Modeling and evaluating data in Tableau
Summary
8
Interpreting Your Results for Your Audience
Interpreting Your Results for Your Audience
Introduction to decision system and machine learning
Decision system-based Bayesian
Bayesian Theory
Fuzzy logic
Building a simple decision system-based Bayesian theory
Integrating a decision system and IoT project
Building your own decision system-based IoT
Summary
References
Index
Index

Advanced Analytics with R and Tableau

Copyright © 2017 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(s), 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: August 2017

Production reference: 1180817

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78646-011-0

www.packtpub.com

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