Getting Started with Business Analytics
Insightful Decision-Making
1st Edition
Published on 26. March 2013
Book
Hardback
190 pages
978-1-4398-9653-2 (ISBN)
Description
Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications.
The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics.
The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data.
The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data.
Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization.
You can check out the book's website here.
The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics.
The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data.
The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data.
Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization.
You can check out the book's website here.
Reviews / Votes
"... an excellent book introducing the essence of business analytics and providing a good summary of the analytical solutions employed across various industries and organizations. ... a solid, accessible overview. It bridges the worlds of business and statistics and describes business analytics from a noncommercial standpoint. It is highly worthy of consideration as supplementary teaching material for students who are taking courses related to business analytics or data mining. Looking back at my teaching career in the field of statistics and business analytics, I confess that it would have been very helpful to have had this kind of book in hand. ... a great guide and a must read for managers, executives, or consultants who want clarity with business analytics."-The American Statistician, February 2015
"... an interesting 'how to get started' book about a contemporary and challenging development in business. ... This timely, accessible book is relevant to students, managers, analysts, executives, consultants, and the general public. Recommended."
-E.J. Szewczak, CHOICE, August 2013
"A must read for college students and business managers interested in big data and analytics. The book beautifully integrates the business and technology aspects of analytics. It provides in-depth know-how to enable the reader to 'know' what and 'how' to effectively leverage analytics to deliver business solutions. If you want to get into business analytics, start your journey here!"
-Ram D. Gopal, Professor and Department Head, School of Business, University of Connecticut
"This book offers an introduction to the essence of business analytics, providing a good summary of the analytical solutions employed across these industries today, including an updated vocabulary on new domains such as social media. The reader will appreciate the difference between supervised and unsupervised learning, k-means clustering and regression tree classification. ... Getting Started with Business Analytics will simplify, and demystify, the concepts around the 'science of data.' Looking back at my career in the field of business analytics, I realize that it would have been extremely helpful to have had such a book in hand. It would have provided me with guidance on structuring my analytical solutions and would have inspired me to greater creativity. I hope this book will light the spark of curiosity for a new generation of data scientists."
-Eric Sandosham, Managing Director and Regional Head of Decision Management at Citibank, Asia Pacific 2010-2012
More details
Language
English
Place of publication
Oxford
United States
Publishing group
Taylor & Francis Inc
Target group
Professional and scholarly
Academic and Professional Practice & Development
Illustrations
66 s/w Abbildungen, 2 s/w Tabellen
2 Tables, black and white; 66 Illustrations, black and white
Dimensions
Height: 260 mm
Width: 183 mm
Thickness: 15 mm
Weight
567 gr
ISBN-13
978-1-4398-9653-2 (9781439896532)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
E-Book
03/2013
1st Edition
Chapman & Hall/CRC
€81.99
Available for download
E-Book
03/2013
1st Edition
Chapman & Hall/CRC
€81.99
Available for download
Persons
David R. Hardoon is the Senior Advisor for Data and Artificial Intelligence at UnionBank Philippines, Chair of Data Committee at Aboitiz Group and acting in capacity of Managing Director for Aboitiz Data Innovation. Concurrently David is an external advisor to Singapore's Corrupt Investigation Practices Bureau (CPIB) in the capacity of Senior Advisor (Artificial Intelligence) and to Singapore's Central Provident Fund Board (CPF) in the capacity of Senior Advisor (Data Science).
David has extensive exposure and experience in both industry and academia and he has consistently applied advanced technology with an analytical mindset to shape and deliver new innovation. David holds a PhD in Computer Science in the field of Machine Learning from the University of Southampton and graduated from Royal Holloway, University of London with First Class Honors B.Sc. in Computer Science and Artificial Intelligence.
Galit Shmueli is Distinguished Professor at the Institute of Service Science, National Tsing Hua University, Taiwan. Between 2011-2014 she was the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics & Information Systems at the Indian School of Business, and earlier Associate Professor of Statistics at University of Maryland's Smith School of Business. She is best known for her research and teaching in business analytics, with a focus on statistical and data mining methods for contemporary data and applications in information systems and healthcare.
Dr. Shmueli's research has been published in the statistics, management, information systems, and marketing literature. She authors over seventy journal articles, books, textbooks and book chapters, including the popular textbook Data Mining for Business Intelligence and Practical Time Series Forecasting. Dr. Shmueli is an award-winning teacher and speaker on data analytics.
David has extensive exposure and experience in both industry and academia and he has consistently applied advanced technology with an analytical mindset to shape and deliver new innovation. David holds a PhD in Computer Science in the field of Machine Learning from the University of Southampton and graduated from Royal Holloway, University of London with First Class Honors B.Sc. in Computer Science and Artificial Intelligence.
Galit Shmueli is Distinguished Professor at the Institute of Service Science, National Tsing Hua University, Taiwan. Between 2011-2014 she was the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics & Information Systems at the Indian School of Business, and earlier Associate Professor of Statistics at University of Maryland's Smith School of Business. She is best known for her research and teaching in business analytics, with a focus on statistical and data mining methods for contemporary data and applications in information systems and healthcare.
Dr. Shmueli's research has been published in the statistics, management, information systems, and marketing literature. She authors over seventy journal articles, books, textbooks and book chapters, including the popular textbook Data Mining for Business Intelligence and Practical Time Series Forecasting. Dr. Shmueli is an award-winning teacher and speaker on data analytics.
Content
Introduction to Business Analytics: The Paradigm Shift. The Business Analytics Cycle. Data Mining and Data Analytics: Data Mining in a Nutshell. From Data Mining to Data Analytics. Business Analytics: Customer Analytics. Social Analytics. Operational Analytics. Bibliography.