Business Analytics Using R - A Practical Approach - Brossura

Hodeghatta, Umesh R R.

Brossura

ISBN 10: 1484225139 ISBN 13: 9781484225134

Casa editrice: Apress, 2016

Riassunto

Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics.

This book will discuss and explore the following through examples and case studies:

• An introduction to R: data management and R functions
  
• The architecture, framework, and life cycle of a business analytics project
  
• Descriptive analytics using R: descriptive statistics and data cleaning
  
• Data mining: classification, association rules, and clustering 
  Predictive analytics: simple regression, multiple regression, and logistic regression 
  

This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book.

What You Will Learn

• Write R programs to handle data

• Build analytical models and draw useful inferences from them

• Discover the basic concepts of data mining and machine learning 

• Carry out predictive modeling

• Define a business issue as an analytical problem

Who This Book Is For

Beginners who want to understand and learn the fundamentals of analytics using R. Students, managers, executives, strategy and planning professionals, software professionals, and BI/DW professionals.

Su questo libro

Informazioni sull?autore

Umesh R. Hodeghatta, Ph.D.

Dr. Umesh Rao. Hodeghatta is an acclaimed professional in the field of machine learning, NLP and business analytics. He has his master’s degree in EE from Oklahoma State University, USA and Ph.D. from the Indian Institute of Technology (IIT), Kharagpur with a specialization in Machine Learning and NLP. Dr. Umesh Hodeghatta is currently  working as a Data Scientist in United States serving multiple clients.  He has more than 20 years of work experience and has held technical and senior management positions at XIM-Bhubaneswar, McAfee, Cisco Systems, and AT&T Bell Laboratories, USA. He has recently established IBM Big Data Analytics Lab and HP Research Lab at Xavier Univeristy. Dr. Hodeghatta has published many journal articles in international journals and conference proceedings, viz, “Understading Twitter as e-WOM”, “Sentiment Analysis of Hollywood Movies on Twitter”, “PCI DSS - Penalty of not being Compliant” are few of the well-known publications. In addition, he has authored a book titled “The InfoSec Handbook: An Introduction to Information Security” published by Springer Apress, USA. Dr. Hodeghatta has contributed his services to many professional organizations and regulatory bodies. He was an Executive Committee member of IEEE Computer Society (India); Academic advisory member for the Information and Security Audit Association (ISACA), USA; IT advisor for the government of Odisha, India; Technical Advisory Member of the International Neural Network Society (INNS) India; Advisory member of Task Force on Business Intelligence & Knowledge Management. Owing to these achievements, he has been listed in "World’s Who’s Who" of the year - 2012, 2013, 2014, 2015 - published by Marquis Who's Who, USA. He is also a senior member of the IEEE, USA. Further details about Dr. Hodeghatta is available at http://www.mytechnospeak.com

Umesha Nayak is a director and principal consultant of MUSA Software Engineering Pvt. Ltd. which focuses on systems / process / management consulting.  He has 33 years’ experience, of which 12 years are in providing consulting to IT / manufacturing and other organizations from across the globe. He is a Master of Science in Software Systems; Master of Arts in Economics; CAIIB; Certified Information Systems Auditor (CISA), and Certified Risk and Information Systems Control (CRISC) professional from ISACA, US; PGDFM; Certified Ethical Hacker from EC Council; Certified Lead Auditor for many of the standards; Certified Coach among others.  He has worked extensively in banking, software development, product design and development, project management, program management, information technology audits, information application audits, quality assurance, coaching, product reliability, human resource management, and consultancy.  He was Vice President and Corporate Executive Council member at Polaris Software Lab, Chennai prior to his current assignment.  He also held various roles like Head of Quality, Head of SEPG and Head of Strategic Practice Unit – Risks & Treasury at Polaris Software Lab.  He started his journey with computers in 1981 with ICL mainframes and continued further with minis and PCs.  He was one of the founding members of the information systems auditing in the banking industry in India.  He has effectively guided many organizations through successful ISO 9001/ISO 27001/CMMI and other certifications and process/product improvements.  He has coauthored the book “The InfoSec Handbook: An Introduction to Information Security” published by Apress Open.

Dalla quarta di copertina

Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics.

This book will discuss and explore the following through examples and case studies:

• An introduction to R: data management and R functions
  
• The architecture, framework, and life cycle of a business analytics project
  
• Descriptive analytics using R: descriptive statistics and data cleaning
  
• Data mining: classification, association rules, and clustering 
  Predictive analytics: simple regression, multiple regression, and logistic regression 
  

This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book.

You will:

• Write R programs to handle data

• Build analytical models and draw useful inferences from them

• Discover the basic concepts of data mining and machine learning 

• Carry out predictive modeling

• Define a business issue as an analytical problem

Dettagli dell?edizione

• Editore: Apress
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 1484225139
• ISBN 13: 9781484225134
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 300
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile