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The guide to targeting and leveraging business opportunities using big data & analytics
By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments.
The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic.
- Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics
- Offers the results of research and the author's personal experience in banking, retail, and government
- Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business
- Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis
For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.
- Sales Rank: #419908 in Books
- Published on: 2014-05-19
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x .90" w x 6.30" l, .97 pounds
- Binding: Hardcover
- 256 pages
From the Inside Flap
A few years ago, big data was little more than a buzzword. Today, it’s a reality for every business, but only a few firms are taking advantage of the new world of information. The science of analytics is a way to get inside customers’ minds and understand the complex behavioral dynamics that affect business. Analytics in a Big Data World advances the discussion of big data by moving it out of the theoretical realm and into everyday business practice.
It has been said that data is the new oil—an abundant resource of great value. The difference between data and oil, as top analytics researcher Bart Baesens understands, is that everyone has data. In areas like risk management, fraud detection, and customer relationship management, the potential gains afforded by big data analytics are well worth exploring. Reading Analytics in a Big Data World is the first step in extracting the valuable information waiting in your databases.
By taking a practitioner’s perspective, this book shows readers how to use the latest developments and new ideas in big data to build an analytics strategy with practical applications. The mathematics and theory have already been tested, so Analytics in a Big Data World draws on case studies and action plans, rather than dwelling unnecessarily on technical details. This realistic focus makes the guide ideal for analytics professionals who want to learn the latest techniques for leveraging data to expand markets.
This latest addition to the Wiley and SAS Business Series is relevant to decisions that all businesses will need to make in the coming years. As the number of practical applications for data skyrockets, learning how to extract business value from big data becomes a competitive requirement. Bart Baesens has accomplished something significant with Analytics in a Big Data World, which delivers an action-oriented guide to staying competitive using the latest analytical models.
From the Back Cover
Praise for Analytics in a Big Data World: The Essential Guide to Data Science and its Applications
“Just by continuously exploiting masses of data, companies like Google, Facebook, Uber, Waze, Zillow, etc. have been able to shake up traditional operating models and industries. Putting the required effort and investment in collecting and exploiting new sets of data is simply a must for competitive advantage. The good news is that today, thanks to the rapidly evolving field of technology, we can collect, store and analyze any type of data at lower cost and faster than ever. With this book, the author provides a unique blend of research and business insights into data science and/or analytics, making it a must read for anyone using these technologies to gain sustainable strategic leverage!”
—Sabine Everaet, Europe CIO, The Coca-Cola Company
“Technology companies today, such as eBay, Amazon, and Facebook, touch large volumes of users and generate massive amounts of data, from transactional to behavioral. An understanding of how to extract value from these massive datasets is critical for all of these companies’ ability to compete for customers. Building upon his profound business expertise and knowledge, the author describes the real-world application of varied data science and analytical techniques that would serve as an excellent guide for analytics professionals as they attempt to use the insights residing in the stores of company data to drive decision-making in their organizations.”
—Steve Metz, Senior Director, Global Customer Experience Finance/Analytics & Collections, eBay
Turn Big Data into Big Opportunities
“Where do we start?” More and more businesses are asking this question as the need to strategically manage data intensifies. Analytics in a Big Data World addresses the seemingly Herculean task of coming to grips with multiple channels of data and sculpting them into quantifiable value. This book is for business professionals who want a focused, practical approach to big data analytics. Analytics researcher Bart Baesens focuses on case studies, real-world application, and steps for implementation, using theory and mathematical formulas only when necessary.
The number of strategic applications for big data is constantly expanding. Analytics in a Big Data World provides an approach to data that can be used in customer relationship management, social media, risk management, and beyond. Past behavior can predict future trends so that you can react more effectively. Learn how to begin describing and predicting customers’ complex behavioral patterns, and find out how to apply your analysis in ways that have been proven to add value and target the bottom line.
Big data sets are assets that can be leveraged quickly and inexpensively. As the science of analytics penetrates every industry in every sector, businesses that fail to use their data assets wisely could fall behind the competition. The flood of new information available to businesses has changed the rules of identifying new business opportunities. Analytics in a Big Data World will help you harness the innovations in data science and address the challenges involved in taming big data.
About the Author
BART BAESENS is an associate professor at KU Leuven (Belgium) and a lecturer at the University of Southampton (United Kingdom), as well as an internationally known data analytics consultant. He is a foremost researcher in the areas of web analytics, customer relationship management, and fraud detection. His findings have been published in well-known international journals including Machine Learning and Management Science. Baesens is also co-author of the book Credit Risk Management: Basic Concepts (Oxford University Press, 2008).
Most helpful customer reviews
2 of 2 people found the following review helpful.
an excellent book which would appeal to academics, students and practitioners that work with the customer-level data
By Galina Andreeva
Bart Baesens’ “Analytics in a Big Data World” is a particularly timely and topical book that provides an easy and well-structured guide to data analysis. Its importance is highlighted in the opening chapter where the need is identified for more experts with analytical skills. This book meets this niche in the market by providing an introductory text for those wishing to educate themselves in the fundamentals of data analysis. It is equally well suited as a supplementary text for business courses that incorporate quantitative methods, and I will be recommending this book to my University library.
The book provides a holistic view of data collection and processing with a very strong practical focus. This discussion of real-life practicalities, such as handling of missing values or target definition, which are seldom touched upon in standard statistical/ machine learning texts, adds a special value.
The book focuses on a customer/individual as data generator, and considers her in a diversity of roles: as a consumer, borrower and part of the community. This highlights the current necessity to analyse the customer in her entirety bringing together huge amounts of disjoint data. I especially liked the chapter on social network analysis, as one of the most recent areas of individual’s digital activity that has not been addressed coherently before. The examples of practical applications towards the end of the book illustrate again various aspects of human activities and associated business problems.
The chapter on methods is concise and yet comprehensive, and the same applies to the entire book. The level of math is appropriate for a reader with some basic statistical knowledge. One thing that I would like to see from a teaching point of view is the list of further recommended reading, e.g. should the reader wish to learn more about linear or logistic regression, what books would be helpful from the author’s point of view. This is, however, a very minor point, and the list of references after each chapter is impressive, it would be good just perhaps, to single out some more ‘educational’ ones.
In summary, it is an excellent book which would appeal to academics, students and practitioners that work with the customer-level data.
5 of 6 people found the following review helpful.
Short review, pretty useless.
By Dimitri K
This is a pretty thin book, which reviews various statistical methods. The Big Data World in the Title is for marketing only, the book does not touch Big data at all. As for statistical methods, they are described briefly, and you will not learn them from this book, maybe except a few simplest. In general, the book was pretty useless for me, only maybe to remind that there are some statistical methods which I need to recall, using other better books.
3 of 4 people found the following review helpful.
A very good book for managers, professionals and students that wish to understand or broaden their knowledge in analytics
By Cris B.
This books presents a clear, concise, and straight-forward introduction to most relevant topics concerning analytics. It is an introductory book in the sense that it discusses all topics without going in depth regarding the underlying mathematical models, but it is done so without neglecting presenting the reader with the most important equations and formulas that are needed for effective decision-making. It covers a wide range of problems and use-cases, from credit scoring to fraud detection and social networks analytics, which are supported by the author's experience in different projects.
Readers that can obtain very good insights from reading this book fall into four categories, in my opinion: managers that wish to understand the added value that analytics could bring to their companies; mid-level executives and analysts that are either starting to use analytics or that are working in analytics projects with consultancy firms and wish to understand the results that the projects will bring to them; established analytics professionals that are looking for new ideas when applying analytics at their firms; and students both at an undergrad and MBA level that are following introductory courses on either Business Intelligence or Business Analytics. For all of them, this book will allow them to quickly get a grasp of most important analytics concepts, and also will present them with many applications where analytics can be used.
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