Автор: Siegel Eric Название: Predictive Analytics ISBN: 1118356853 ISBN-13(EAN): 9781118356852 Издательство: Wiley Рейтинг: Цена: 15830 T Наличие на складе: Поставка под заказ. Описание:
"The "Freakonomics" of big data." --Stein Kretsinger, founding executive of Advertising.com
Award-winning - Used by over 30 universities - Translated into 9 languages
"An introduction for everyone. ""In this rich, fascinating -- surprisingly accessible -- introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day. Rather than a "how to" for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques."
Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing "unnatural" resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise This heap of refuse is a gold mine. "Big data" embodies an extraordinary wealth of experience from which to learn." Predictive Analytics" unleashes the power of data. With this technology," " the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction -- "now in its Revised and Updated edition" -- former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death -- including one health insurance company. How U.S. Bank and Obama for America calculated -- and Hillary for America 2016 plans to calculate -- the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used "predictive modeling" to answer questions and beat the human champs on TV's "Jeopardy " How companies ascertain untold, private truths -- how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 183 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more.
How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more.""
A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it -- or consumed by it -- get a handle on the power of "Predictive Analytics."
Автор: Baesens Bart, Verbeke Wouter, Van Vlasselaer Veron Название: Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection ISBN: 1119133122 ISBN-13(EAN): 9781119133124 Издательство: Wiley Рейтинг: Цена: 32520 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution.
Автор: Heckmann Название: Towards Supply Chain Risk Analytics ISBN: 3658148691 ISBN-13(EAN): 9783658148690 Издательство: Springer Рейтинг: Цена: 80910 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this thesis, Iris Heckmann develops a profound conceptual basis of supply chain risk analytics. She transfers the newly defined concepts for the modelling and operationalization of supply chain risk within simulation and optimization approaches, in order to ease unexpected deviations and disruptions, which are subsumed under the notion of supply chain risk, increasingly aggravating the planning and optimization of supply chains.
Автор: Jac Fitz?€“enz,John Mattox II Название: Predictive Analytics for Human Resources ISBN: 1118893670 ISBN-13(EAN): 9781118893678 Издательство: Wiley Рейтинг: Цена: 32520 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Create and run a human resource analytics project with confidence For any human resource professional that wants to harness the power of analytics, this essential resource answers the questions: "Where do I start?" and "What tools are available?" Predictive Analytics for Human Resources is designed to answer these and other vital questions.
Автор: Burke J Название: Health Analytics ISBN: 1118383044 ISBN-13(EAN): 9781118383049 Издательство: Wiley Рейтинг: Цена: 41680 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A hands-on, analytics road map for health industry leaders The industry-wide transformation taking place across the health and life sciences ecosystem is mandating that organizations adopt new decision-making capabilities, based on science and real-world information.
Автор: Chorianopoulos Antonios Название: Effective CRM Using Predictive Analytics ISBN: 1119011558 ISBN-13(EAN): 9781119011552 Издательство: Wiley Рейтинг: Цена: 38310 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A step-by-step guide to data mining applications in CRM. Following a handbook approach, this book bridges the gap between analytics and their use in everyday marketing, providing guidance on solving real business problems using data mining techniques. The book is organized into three parts.
Автор: Bullard Brittany Название: Style and Statistics: The Art of Retail Analytics ISBN: 1119270316 ISBN-13(EAN): 9781119270317 Издательство: Wiley Рейтинг: Цена: 31670 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A non-technical guide to leveraging retail analytics for personal and competitive advantage Style & Statistics is a real-world guide to analytics in retail.
Автор: Hui Yang,Eva K. Lee Название: Healthcare Analytics: From Data to Knowledge to Healthcare Improvement ISBN: 1118919394 ISBN-13(EAN): 9781118919392 Издательство: Wiley Рейтинг: Цена: 89990 T Наличие на складе: Поставка под заказ. Описание: Features statistical and operational research methods and tools being used to improve the healthcare industry With a focus on cutting–edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data–driven healthcare analytics in an effort to provide more personalized and efficient healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance care quality and operational efficiency. Organized into two main sections, Part One features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part Two focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician–patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features: Contributions from well–known international experts who shed light on new approaches in this growing area Discussions on contemporary methods and techniques to address the handling of rich and large–scale healthcare data as well as the overall optimization of healthcare system operations Numerous real–world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry Plentiful applications that showcase the various analytical methods and tools that can be applied to successful predictive modeling The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate–level courses typically offered within operations research, industrial engineering, business, and public health departments. Hui Yang, PhD, is Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University. His research interests include sensor–based modeling and analysis of complex systems for process monitoring/control; system diagnostics/prognostics; quality improvement; and performance optimization with special focus on nonlinear stochastic dynamics and the resulting chaotic, recurrence, self–organizing behaviors. Eva K. Lee, PhD, is Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, Director of the Center for Operations Research in Medicine and HealthCare, and Distinguished Scholar in Health System, Health Systems Institute at both Emory University School of Medicine and Georgia Institute of Technology. Her research interests include health risk prediction; early disease prediction and diagnosis; optimal treatment strategies and drug delivery; healthcare outcome analysis and treatment prediction; public health and medical preparedness; large–scale healthcare/medical decision analysis and quality improvement; clinical translational science; and business intelligence and organization transformation.
Автор: McGuire Kelly Название: The Analytic Hospitality Executive: Implementing Data Analytics in Hotels and Casinos ISBN: 1119129982 ISBN-13(EAN): 9781119129981 Издательство: Wiley Рейтинг: Цена: 29170 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Targeted analytics to address the unique opportunities in hospitality and gaming The Analytic Hospitality Executive helps decision makers understand big data and how it can drive value in the industry.
Автор: Chase Charles W. Название: Next Generation Demand Management: People, Process, Analytics, and Technology ISBN: 1119186633 ISBN-13(EAN): 9781119186632 Издательство: Wiley Рейтинг: Цена: 31670 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A practical framework for revenue-boosting supply chain management Next Generation Demand Management is a guidebook to next generation Demand Management, with an implementation framework that improves revenue forecasts and enhances profitability.
Автор: Gupta Название: Interview Questions in Business Analytics ISBN: 1484206002 ISBN-13(EAN): 9781484206003 Издательство: Springer Рейтинг: Цена: 22030 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Discover relevant questions—and detailed answers—to help you prepare for job interviews and break into the field of analytics. This book contains more than 200 questions based on consultations with hiring managers and technical professionals already working in analytics. Interview Questions in Business Analytics: How to Ace Interviews and Get the Job You Want fills a gap in information on business analytics for job seekers. Bhasker Gupta, the founder and editor of Analytics India Magazine, has come up with more than 300 questions job applicants are likely to face in an interview. Covering data preparation, statistics, analytics implementation, as well as other crucial topics favored by interviewers, this book:Provides 300+ interview questions often asked by recruiters and hiring managers in global corporationsOffers short and to-the-point answers to the depth required, while looking at the problem from all angles Provides a full range of interview questions for jobs ranging from junior analytics to senior data scientists and managersOffers analytics professionals a quick reference on topics in analyticsUsing a question-and-answer format from start to finish, Interview Questions in Business Analytics: How to Ace Interviews and Get the Job You Want will help you grasp concepts sooner and with deep clarity. The book therefore also serves as a primer on analytics and covers issues relating to business implementation. You will learn about not just the how and what of analytics, but also the why and when. This book will thus ensure that you are well prepared for interviews—putting your dream job well within reach.Business analytics is currently one of the hottest and trendiest areas for technical professionals. With the rise of the profession, there is significant job growth. Even so, it’s not easy to get a job in the field, because you need knowledge of subjects such as statistics, databases, and IT services. Candidates must also possess keen business acumen. What's more, employers cast a cold critical eye on all applicants, making the task of getting a job even more difficult.What You'll LearnThe 300 questions in this book cover such topics as:• The different types of data used in analytics• How analytics are put to use in different industries• The process of hypothesis testing • Predictive vs. descriptive analytics• Correlation, regression, segmentation and advanced statistics• Predictive modelingWho This Book Is ForThose aspiring to jobs in business analytics, including recent graduates and technical professionals looking for a new or better job. Job interviewers will also find the book helpful in preparing interview questions.
Автор: Corea Название: Big Data Analytics: A Management Perspective ISBN: 3319389912 ISBN-13(EAN): 9783319389912 Издательство: Springer Рейтинг: Цена: 88260 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth strategies, etc.). The important matter of selecting the right skills and people for an effective team will be extensively explained, and practical ways to recognize them and understanding their personalities will be provided. Finally, few relevant technological future trends will be acknowledged (i.e., IoT, Artificial intelligence, blockchain, etc.), especially for their close relation with the increasing amount of data and our ability to analyse them faster and more effectively.
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