: Umesh Hodeghatta Rao, Umesh Nayak
: Business Analytics Using R - A Practical Approach
: Apress
: 9781484225141
: 1
: CHF 53.20
:
: Datenkommunikation, Netzwerke
: English
: 291
: Wasserzeichen/DRM
: PC/MAC/eReader/Tablet
: PDF

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 Rhelps 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
  • Descripti e analytics using R: descriptive statistics and data cleaning
  • Data mining: classification, association rules, and clustering 
    Predictiv 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

Beginne s 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.



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< p>


Umes a 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.


Contents at a Glance4
Contents5
About the Authors15
About the Technical Reviewer17
Chapter 1: Overview of Business Analytics18
1.1 Objectives of This Book20
1.2 Confusing Terminology21
1.3 Drivers for Business Analytics22
1.3.1 Growth of Computer Packages and Applications23
1.3.2 Feasibility to Consolidate Data from Various Sources24
1.3.3 Growth of Infinite Storage and Computing Capability24
1.3.4 Easy-to-Use Programming Tools and Platforms24
1.3.5 Survival and Growth in the Highly Competitive World24
1.3.6 Business Complexity Growing out of Globalization25
1.4 Applications of Business Analytics25
1.4.1 Marketing and Sales25
1.4.2 Human Resources26
1.4.3 Product Design26
1.4.4 Service Design26
1.4.5 Customer Service and Support Areas26
1.5 Skills Required for a Business Analyst27
1.5.1 Understanding the Business and Business Problems27
1.5.2 Understanding Data Analysis Techniques and Algorithms27
1.5.3 Having Good Computer Programming Knowledge28
1.5.4 Understanding Data Structures and Data Storage/Warehousing Techniques28
1.5.5 Knowing Relevant Statistical and Mathematical Concepts28
1.6 Life Cycle of a Business Analytics Project28
1.7 The Framework for Business Analytics31
1.8 Summary32
Chapter 2: Introduction to R33
2.1 Data Analysis Tools33
2.2 R Installation37
2.2.1 Installing R37
2.2.2 Installing RStudio39
2.2.3 Exploring the RStudio Interface39
2.3 Basics of R Programming41
2.3.1 Assigning Values42
2.3.2 Creating Vectors43
2.4 R Object Types43
2.5 Data Structures in R45
2.5.1 Matrices46
2.5.2 Arrays47
2.5.3 Data Frames48
2.5.4 Lists50
2.5.5 Factors51
2.6 Summary52
Chapter 3: R for Data Analysis53
3.1 Reading and Writing Data53
3.1.1 Reading Data from a Text File54
3.1.2 Reading Data from a Microsoft Excel File58
3.1.3 Reading Data from the Web60
3.2 Using Control Structures in R61
3.2.1 if-else62
3.2.2 for loops62
3.2.3 while loops63
3.2.4 Looping Functions64
3.2.4.1 apply( )65
3.2.4.2 lapply( )66
3.2.4.3 sapply( )67
3.2.4.4 tapply( )67
3.2.4.5 cut( )69
3.2.4.6 split( )70
3.2.5 Writing Your Own Functions in R71
3.3 Working with R Packages and Libraries72
3.4 Summary74
Chapter 4: Introduction to descriptive analytics75
4.1 Descriptive analytics78
4.2 Population and sample78
4.3 Statistical parameters of interest79
4.3.1 Mean80
4.3.2 Median82
4.3.3 Mode84
4.3.4 Range84
4.3.5 Quantiles85
4.3.6 Standard deviation86
4.3.7 Variance89
4.3.8 Summary command in R89
4.4 Graphical description of the data90
4.4.1 Plots in R90
4.4.2 Histogram93
4.4.3 Bar plot93
4.4.4 Boxplots94
4.5 Computations on data frames95
4.5.1 Scatter plot97