Описание: Now, a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications.
Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes:
The role of analytics in delivering effective messages on the web
Understanding the web by understanding its hidden structures
Being recognized on the web - and watching your own competitors
Visualizing networks and understanding communities within them
Measuring sentiment and making recommendations
Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics
Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.
Автор: S. Finlay Название: Predictive Analytics, Data Mining and Big Data ISBN: 1349478687 ISBN-13(EAN): 9781349478682 Издательство: Springer Рейтинг: Цена: 4890.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.
Автор: Vincenzo Morabito Название: Big Data and Analytics ISBN: 3319106643 ISBN-13(EAN): 9783319106649 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars.
Автор: Vincenzo Morabito Название: Big Data and Analytics ISBN: 3319364766 ISBN-13(EAN): 9783319364766 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars.
Автор: Skillicorn, David B. Название: Cyberspace, data analytics, and policing ISBN: 036764276X ISBN-13(EAN): 9780367642761 Издательство: Taylor&Francis Рейтинг: Цена: 10258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Cyberspace, Data Analytics, and Policing surveys the changes that cyberspace has brought to criminality and to policing with enough technical content to expose the issues and suggest ways in which law enforcement organizations can adapt.
Автор: Sang C. Suh; Thomas Anthony Название: Big Data and Visual Analytics ISBN: 3319639153 ISBN-13(EAN): 9783319639154 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics.
Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics.
This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.
Описание: This book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems.
Автор: Tavana Название: Recent Developments in Data Science and Business Analytics ISBN: 3319727443 ISBN-13(EAN): 9783319727448 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Part I Marketing and Supply Chain Analytics: Chapter1: Research on Differential Pricing and Coordination Mechanism of Second-Class Supply Chain of New Products and Remanufactured Products.- Chapter2: A study on Cooperation Strategies of Dual Channel Supply Chain Based on Service Level.- Chapter3: The Quality Management of Food Supply Chain in Perspective of Food Safety.- Chapter4: Strategic Customer Behavior with Risk Preference for a Supply Chain Management Based on Double Channel.- Chapter5: Competition and Coordination in Single-supplier Multiple-retailer Supply Chain.- Chapter6: Research on the Construction of Enterprise Brand Competitiveness Evaluation System Based on the Integration of SWOT and AHP Model.- Chapter7: Reflections on the Training Mode of E-commerce Professionals with improved Practical Exercises and Innovative Ability.- Chapter8: Research on Evaluating Marketing Ability of Traditional Chinese Medicine Enterprises in Gansu Province.- Part II: Logistics and Operations Analytics: Chapter9: The Impact of the Relationship between Operational Cost and Oil Prices on Economic Assessment in Oil and Gas Industry.- Chapter10: The Construction of University Students' Entrepreneurship Competency Model in Application-Oriented Universities.- Chapter11: Improving Airport Security Screening System in Terms of Efficiency and Fairness Via Network Model.- Chapter12: Study on the Choice of Strategic Emerging Industries in Gansu Province Based on Multi-level Grey Model.- Chapter13: The Study of "Big Quality" Satisfaction Evaluation.- Chapter14: Research on Evaluation Index System of Enterprise Brand Competitiveness - Taking Liquor Industry as an Example.- Chapter15: Simulation of Stochastic Volatility Variance Swap.- Chapter16: Empirical Research of the Contribution Rate of University Science and Technology to the Regional Economic Development.- Chapter17: Research on Incentive Strategy of Logistics Outsourcing about Manufacturing Enterprises.- Chapter18: Research on External Quality Inspection Technology of Tropical Fruits Based on Computer Vision.- Chapter19: Wholesale Price Contract and Quantity Discount Contract under Competition with Various Games.- Chapter20: Evaluation of Science and Technology Service Industry in Shandong Province.- Part III: Financial Analytics: Chapter21: CEO's Background Characteristics, Financing Preference and Firm Performance-----Empirical Evidence from China's A-share Listed Companies.- Chapter22: Security Risk Management Approach for Improving Information Security Return of Investment.- Chapter23: Comparative Analysis on Investment and Financing Models of Urban Rail Transportation.- Chapter24: Measuring Systemic Risk in the Chinese Financial System Based on Asymmetric Exponential Power Distribution.- Chapter25: Research on Liquidity Preferences of Mutual Fund.- Chapter26: Relationship of the Financial Agglomeration and Fiscal Expenditure Scale of Yangtze River Delta.- Chapter27: Applying Data Processing Method for Relationship Discovery in the Stock Market.- Chapter28: A Study on Assets Categorizations and Optimal Allocation via an Improved Algorithm.- Chapter29: Forecasting Stock Price Index Volatility with LSTM Deep Neural Network.- Chapter30: Improvement of Hedging Effect Based on the Average Hedging Ratio.- Chapter31: Finding the Lenders of Bad Credit Score Based on the Classification Method.- Part IV: Chapter32: Research Status and Prospect of Data Extraction and Cleaning Technology in Large Environment.- Chapter33: Research on Intelligent Sales Platform of Automobile Industry Based on Large Data Mining.- Chapter34: A Local Neighborhood Constraint Method for SIFT Features Matching.- Chapter35: A Wine Consumption Prediction Model Based on L-DAGLSSVM.- Chapter36: Fuzzy Control and Network System Design for Time Series Prediction Model.- Chapter37: Research on Data Storage Based on Cloud Platform.- Chapter38: An Automatic Multi-Objective Clustering based on Hierarchical Method
Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.
Автор: Shinde, Gitanjali Rahul (department Of Computer Engineering, Stes`s, Smt. Kashibai Navale College Of Engineering, Pune, India) Kalamkar, Asmita Balasa Название: Data analytics for coronavirus disease (covid-19) outbreak ISBN: 0367558467 ISBN-13(EAN): 9780367558468 Издательство: Taylor&Francis Рейтинг: Цена: 8726.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The focus of this book is data analytics for COVID-19 which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussion on data models, their performance, different Big data techniques, tools and technologies.
Автор: C. Keith Harrison, Scott Bukstein Название: Sport Business Analytics ISBN: 1498761267 ISBN-13(EAN): 9781498761260 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Поставка под заказ.
Описание:
Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group.
The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in:
Ticket pricing
Season ticket member retention
Fan engagement
Sponsorship valuation
Customer relationship management
Digital marketing
Market research
Data visualization.
This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations.
Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.
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