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

Modeling and evaluating data in Tableau

Neural networks are often difficult to understand. When the data is loaded into Tableau, we can visually understand the distinctions made by the underlying model. Since we can easily load data into Tableau, we can do this on an ongoing basis.

In this example, we will use Tableau as part of the testing process. We will present the model with data, and see how well the R model can distinguish between the three types of iris. Once we have set up the Tableau workbook, we can load more data into the workbook, using the connect to data facility. This would help us to see if the model continues to distinguish between the model types, and we could continue to test the model on an ongoing basis.

Using Tableau to evaluate data

Let's load more data into Tableau. For our testing purposes, we will reuse the iris data that we used in the earlier example. However, if this was real life, this would not be the best practice for testing purposes. Here, we are reusing the...