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.
Table of Contents (16 chapters)
Advanced Analytics with R and Tableau
About the Authors
About the Reviewers
Customer Feedback

Business understanding

When we are modeling data, it is crucial to keep the original business objectives in mind. These business objectives will direct the subsequent work in the data understanding, preparation and modeling steps, and the final evaluation and selection (after revisiting earlier steps if necessary) of a classification model or models.

At later stages, this will help to streamline the project because we will be able to keep the model's performance in line with the original requirement, while retaining a focus on ensuring a return on investment from the project.

The main business objective is to identify individuals who are higher earners, so that they can be targeted by a marketing campaign. For this purpose, we will investigate the data mining of demographic data in order to create a classification model in R. The model will be able to accurately determine whether individuals earn a salary that is above or below $50K per annum. The datasets used in this chapter were taken from...