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Analytics in a Big Data World: The Essential Guide to Data Science and its Applications (Wiley and SAS Business Series) Hardcover – May 19, 2014
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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.
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Top Customer Reviews
Dr. Goutam Chakraborty, Professor(Marketing) and Director of Graduate Certificate Program Business Data Mining, Director of Graduate Certificate Program Marketing Analytics, Oklahoma State University (analytics.okstate.edu)
The book provides detailed expertise in three applications that seldom appear together: churn prediction (usually seen as a CRM/quantitative marketing task), credit risk (mostly covered in financial books), and social network analysis, another hot topic which has been studied mainly in the field of computer science. These applications are studied under a unifying framework, together with the most suitable techniques for each task. Traditional statistic/econometric methods such as logistic regression and survival analysis, and machine learning approaches, such as Support Vector Machines and Self Organized Maps, are studied jointly. The descriptions of the methods are easy to follow, although a basic knowledge of statistics is necessary. The sections I enjoyed the most were the last two chapters, in which the author shares his vast expertise in the applications mentioned.
In summary, “Analytics in a Big Data World” is an intermediate book which will allow you to understand the most important methods used in analytics while providing tips for the successful implementation of your BI projects. It is also a great guide for teaching/learning business analytics courses.