R for Cloud Computing looks at some of the tasks performed by business analysts on the desktop (PC era) and helps the user navigate the wealth of information in R and its 4000 packages as well as transition the same analytics using the cloud. With this information the reader can select both cloud vendors and the sometimes confusing cloud ecosystem as well as the R packages that can help process the analytical tasks with minimum effort, cost and maximum usefulness and customization. The use of Graphical User Interfaces (GUI) and Step by Step screenshot tutorials is emphasized in this book to lessen the famous learning curve in learning R and some of the needless confusion created in cloud computing that hinders its widespread adoption. This will help you kick-start analytics on the cloud including chapters on both cloud computing, R, common tasks performed in analytics including the current focus and scrutiny of Big Data Analytics, setting up and navigating cloud providers.
Readers are exposed to a breadth of cloud computing choices and analytics topics without being buried in needless depth. The included references and links allow the reader to pursue business analytics on the cloud easily. It is aimed at practical analytics and is easy to transition from existing analytical set up to the cloud on an open source system based primarily on R.
This book is aimed at industry practitioners with basic programming skills and students who want to enter analytics as a profession. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. It will also help researchers and academics but at a practical rather than conceptual level.
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. The cloud computing paradigm is firmly established as the next generation of computing from microprocessors to desktop PCs to cloud.
Rezensionen / Stimmen
From the book reviews:
"The book is opening for experimentation and thought. It is full of practical examples, tons of relevant reference. . is targeting a mature R user who wants to expand one's horizons or a corporate decision maker willing to take one's enterprise one notch . further ahead in the game. . A deserving read, even though more like a collection of stories and collection of technologies. A possibly convincing approach and sure inspiring to take the R community to new heights." (Z. Arthur, Compudicted, compudicted.wordpress.com, December, 2014)
Auflage
Sprache
Verlagsort
Zielgruppe
Für Beruf und Forschung
Professional/practitioner
Illustrationen
160
95 s/w Abbildungen, 160 farbige Abbildungen
XVII, 267 p. 255 illus., 160 illus. in color.
Maße
Höhe: 235 mm
Breite: 155 mm
Dicke: 15 mm
Gewicht
ISBN-13
978-1-4939-1701-3 (9781493917013)
DOI
10.1007/978-1-4939-1702-0
Schweitzer Klassifikation
Ajay Ohri is the founder of analytics startup Decisionstats.com. He has pursued graduate courses at the University of Tennessee, Knoxville and completed a Masters from Indian Institute of Management, Lucknow. Ohri also has a mechanical engineering degree from the Delhi College of Engineering. He has interviewed more than 150 practitioners in analytics, including leading members from all the analytics software vendors. Ohri has written almost 2000 articles on his blog, in addition to writing about APIs for influential websites like ProgrammableWeb. Ohri's current research interests include spreading open source analytics, analysing social media manipulation with mechanism design, simpler interfaces to cloud computing, investigating climate change manipulation and unorthodox cryptography including visual and quantum. He is currently advising multiple start ups in analytics off shoring, analytics services, and analytics education as well as using social media to enhance buzz for analytics products. Ajay works with R, SAS, Julia and Python languages and finds beauty in all of them.
Introduction.- An Approach for Data Scientists.- Navigating the Choices in R and Cloud Computing.- Setting up R on the Cloud.- Using R.- Using R with Data and Bigger Data.- R with Cloud APIs.- Securing your R Cloud.- Training Literature for Cloud Computing and R.
