Advanced Analytics with R and Tableau

Advanced Analytics with R and Tableau

by Ruben Oliva Ramos and Jen Stirrup
English | 2017 | ISBN: 1786460114 | 178 Pages | ePUB | 3.18 MB

This book will appeal to Tableau users who want to go beyond the Tableau interface and deploy the full potential of Tableau, by using R to perform advanced analytics with Tableau.

A basic familiarity with R is useful but not compulsory, as the book will start off with concrete examples of R and will move quickly into more advanced spheres of analytics using online data sources to support hands-on learning. Those R developers who want to integrate R in Tableau will also benefit from this book.

What You Will Learn:

- Integrate Tableau's analytics with the industry-standard, statistical prowess of R.
- Make R function calls in Tableau, and visualize R functions with Tableau using RServe.
- Use the CRISP-DM methodology to create a roadmap for analytics investigations.
- Implement various supervised and unsupervised learning algorithms in R to return values to Tableau.
- Make quick, cogent, and data-driven decisions for your business using advanced analytical techniques such as forecasting, predictions, association rules, clustering, classification, and other advanced Tableau/R calculated field functions.

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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