The first collection of cases on "big data" analytics for supply chain, operations research, and operations management, this reference puts readers in the position of the analytics professional and decision-maker. Perfect for students, practitioners, and certification candidates in SCM, OM, and OR, these short, focused, to-the-point case studies illustrate the entire decision-making process. They provide realistic opportunities to perform analyses, interpret output, and recommend an optimal course of action. Contributed by leading "big data" experts, the cases in The Applied Business Analytics Casebook covers: Forecasting and statistical analysis: time series forecasting models, regression models, data visualization, and hypothesis testing Optimization and simulation: linear, integer, and nonlinear programming; Monte Carlo simulation and risk analysis; and stochastic optimization Decision analysis: decision making under uncertainty; expected value of perfect information; decision trees; game theory models; AHP; and multi-criteria decision making Advanced business analytics: data warehousing/mining; text mining; neural networks; financial analytics; CRM analytics; and revenue management models

If you're seeking to master business analytics, case studies offer invaluable help: they expose you to the entire decision-making process, helping you practice an active role in both performing analysis and using its output to recommend optimal decisions. Now, drawing on his extensive teaching and consulting experience, Prof. Matthew Drake has created the ideal new casebook for all analytics students and practitioners. Drake, author of the widely-praised Applied Business Analytics Casebook, now presents a collection of up-to-date cases that are longer and more detailed than those typically presented in undergraduate texts, but concise and focused enough to be taught in a single classroom session. Organized by analytical technique, Advances in Business, Operations, and Product Analytics covers: Descriptive analytics: descriptive statistics, sampling/inferential statistics, statistical quality control, and probability Predictive analytics: forecasting, demand managing, data and text mining Prescriptive analytics: optimization-based modeling, simulation-based modeling, decision analysis, and multi-criteria decision making Industry-specific analytics: HR and managerial analytics, financial analytics, and healthcare/life sciences In addition to practitioners, this casebook will be especially valuable to students and faculty in undergraduate and masters' courses that cover topics in business analytics, and courses applying analytics to specific industries such as healthcare, or specific business functions such as marketing.

As business becomes increasingly complex and global, decision-makers must act more rapidly and accurately, based on the best available evidence. Modern data mining and analytics is indispensable for doing this. Real-World Data Mining demystifies current best practices, showing how to use data mining and analytics to uncover hidden patterns and correlations, and leverage these to improve all business decision-making. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, Delen provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: data mining processes, methods, and techniques; the role and management of data; tools and metrics; text and web mining; sentiment analysis; and integration with cutting-edge Big Data approaches. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials.

The American way of producing health is failing. It continues to rank very low among developed countries on our most vital need...to live a long and healthy life. Despite the well-intentioned actions on the part of government, life sciences, and technology, the most important resource for achieving our full health potential is ourselves. This book is about how you can do so, and how others can help you. Dwight McNeill introduces person-centered health analytics (pchA) and shows how you can use it to master five everyday behaviors that cause and perpetuate most chronic diseases. Using Person-Centered Health Analytics to Live Longer combines deep insight, a comprehensive framework, and practical tools for living longer and healthier lives. It offers a clear path forward for both individuals and stakeholders, including providers, payers, health promotion companies, technology innovators, government, and analytics practitioners.

Will "Big Data" supercharge the economy, tyrannize us, or both? Data Exhaust is the definitive primer for everyone who wants to understand all the implications of Big Data, digitally driven innovation, and the accelerating Internet Economy. Renowned digital expert Dale Neef clearly explains: What Big Data really is, and what's new and different about it How Big Data works, and what you need to know about Big Data technologies Where the data is coming from: how Big Data integrates sources ranging from social media to machine sensors, smartphones to financial transactions How companies use Big Data analytics to gain a more nuanced, accurate picture of their customers, their own performance, and the newest trends How governments and individual citizens can also benefit from Big Data How to overcome obstacles to success with Big Data - including poor data that can magnify human error A realistic assessment of Big Data threats to employment and personal privacy, now and in the future Neef places the Big Data phenomenon where it belongs: in the context of the broader global shift to the Internet economy, with all that implies. By doing so, he helps businesses plan Big Data strategy more effectively - and helps citizens and policymakers identify sensible policies for preventing its misuse. By conservative estimate, the global Big Data market will soar past $50 billion by 2018. But those direct expenses represent just the "tip of the iceberg" when it comes to Big Data's impact. Big Data is now of acute strategic interest for every organization that aims to succeed - and it is equally important to everyone else. Whoever you are, Data Exhaust tells you exactly what you need to know about Big Data - and what to do about it, too.

The book describes advanced business analytics and shows how to apply them to many different professional areas of engineering and management. Each chapter of the book is contributed by a different author and covers a different area of business analytics. The book connects the analytic principles with business practice and provides an interface between the main disciplines of engineering/technology and the organizational, administrative and planning abilities of management. It also refers to other disciplines such as economy, finance, marketing, behavioral economics and risk analysis. This book is of special interest to engineers, economists and researchers who are developing new advances in engineering management but also to practitioners working on this subject.