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

Chapter 3. A Methodology for Advanced Analytics Using Tableau and R

In the era of big data when lack of methodology is likely to produce random and false discoveries, a robust framework for delivery is extremely important. According to a Dataversity poll in 2015, it was found that only 17% of survey respondents said they had a well-developed Predictive or Prescriptive Analytics program in place. On the other hand, 80% of respondents said they planned on implementing such a program within five years. How can we ensure that our projects are successful?

There is an increasing amount of data in the world, and in our databases. The data deluge is not going to go away anytime soon! Businesses risk wasting the useful business value of information contained in databases, unless they are able to excise useful knowledge from the data.

There is a saying in the world of data: garbage in, garbage out. Data needs to be cleaned before it is turned into information. There is a difference between original...