R for Business Analytics

ISBN-13: 9781493942398 / Angielski / Miękka / 2016 / 312 str.

Ajay Ohri; A. Ohri

Opis

This book examines common tasks performed by business analysts and helps the reader navigate the wealth of information in R and its 4000 packages to create useful analytics applications. Includes interviews with corporate users of R, and easy-to-use examples.

Recenzje

From the book reviews:

"This book focuses on how to use R software for basic statistics in a business context. ... The use of GUIs in this book exposes the reader to some of the power of R for business planning and decision making in a user-friendly environment. ... The content of this book is light from a statistical point of view, but does serve to provide a nice overview of GUIs that are helpful for anyone doing business analytics in R." (Roger M. Sauter, Technometrics, Vol. 55 (3), August, 2013)

"I am enjoying reading this book. ... After reading this book I feel more confident about getting data into R. ... Each chapter has a summary at the end listing all the packages and functions used in the chapter. ... a very useful book on business analytics." (Cats and Dogs with Data, maryannedata.wordpress.com, August, 2013)

"If you are a beginner like me and want to learn everything about R and don't know where to begin, then this book will do you wonders. It has everything you need to get started. This book will be your companion and will not disappoint you." (The R Blabber, May, 2013)

"The book has something for both beginning R users (who may be experienced in data science, but want to start learning how to apply R towards their field), and experienced R users ... . the book has an extremely broad coverage of R's many packages that can be used towards business data analysis, with a very hands on approach that can help many new users quickly come up to speed and running on utilizing R's powerful capabilities." (Intelligent Trading Tech, October, 2012)

Spis treści

Why R.- R Infrastructure.- R Interfaces.- Manipulating Data.- Exploring Data.- Building Regression Models.- Data Mining using R.- Clustering and Data Segmentation.- Forecasting and Time-Series Models.- Data Export and Output.- Optimizing your R Coding.- Additional Training Literature.- Appendix.

O autorze

Ajay Ohri is the founder of analytics startup Decisionstats.com.  He has pursued graduate studies at the University of Tennessee, Knoxville and the Indian Institute of Management, Lucknow.  In addition, Ohri has a mechanical engineering degree from the Delhi College of Engineering. He has interviewed more than 100 practitioners in analytics, including leading members from all the analytics software vendors.  Ohri has written almost 1300 articles on his blog, besides guest writing for influential analytics communities. He teaches courses in R through online education and has worked as an analytics consultant in India for the past decade. Ohri was one of the earliest independent analytics consultant in India, and his current research interests include spreading open source analytics, analyzing social media manipulation, simpler interfaces to cloud computing and unorthodox cryptography.

Blurb

R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages.  With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics. 

 

This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy.