Synopsis
Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of R
About This Book
- A comprehensive guide that will bring out the creativity in you to visualize the results of complex calculations using Tableau and R
- Combine Tableau analytics and visualization with the power of R using this step-by-step guide
- Wondering how R can be used with Tableau? This book is your one-stop solution.
Who This Book Is For
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.
In Detail
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.
Style and approach
Tableau (uniquely) offers excellent visualization combined with advanced analytics; R is at the pinnacle of statistical computational languages. When you want to move from one view of data to another, backed up by complex computations, the combination of R and Tableau makes the perfect solution. This example-rich guide will teach you how to combine these two to perform advanced analytics by integrating Tableau with R and create beautiful data visualizations.
About the Authors
Jen Stirrup, recently named as one of the top 9 most influential business intelligence female experts in the world by Solutions Review, is a Microsoft Data. Platform MVP, and PASS Director-At-Large, is a well-known business intelligence and data visualization expert, author, data strategist, and community advocate who has been peer-recognized as one of the top 100 most global influential tweeters on big data and analytics topics. Specialties: business intelligence, Microsoft SQL Server, Tableau, architecture, data, R, Hadoop, and Hive. Jen is passionate about all things data and business intelligence, helping leaders derive value from data. For two decades, Jen has worked in artificial intelligence and business intelligence consultancy, architecting, and delivering and supporting complex enterprise solutions for customers all over the world.
Ruben Oliva Ramos is a computer systems engineer from Tecnologico of Leon Institute with a master's degree in computer and electronic systems engineering, tele informatics, and networking specialization from University of Salle Bajio in Leon, Guanajuato, Mexico. He has more than five years' experience in developing web applications to control and monitor devices connected with the Arduino and Raspberry Pi using web frameworks and cloud services to build Internet of Things applications. He is a mechatronics teacher at University of Salle Bajio and teaches students studying for their master's degree in Design and Engineering of Mechatronics Systems. He also works at Centro de Bachillerato Tecnologico Industrial 225 in Leon, Guanajuato, Mexico, teaching electronics, robotics and control, automation, and microcontrollers at Mechatronics Technician Career. He has worked on consultant and developer projects in areas such as monitoring systems and datalogger data using technologies such as Android, iOS, Windows Phone, Visual Studio .NET, HTML5, PHP, CSS, Ajax, JavaScript, Angular, ASP .NET databases (SQLite, MongoDB, and MySQL), and web servers (Node.js and IIS). Ruben has done hardware programming on the Arduino, Raspberry Pi, Ethernet Shield, GPS, and GSM/GPRS, ESP8266, control and monitor systems for data acquisition and programming. He's the Author at Pack Publishing book: Internet of Things Programming with JavaScript.
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