Data-Enabled Analytics: Dea for Big Data, Zhu Joe, Charles Vincent
Автор: Miller Thomas W. Jr. Название: Marketing Data Science: Modeling Techniques in Predictive Analytics with Python and R ISBN: 0133886557 ISBN-13(EAN): 9780133886559 Издательство: Pearson Education Рейтинг: Цена: 78530.00 T Наличие на складе: Поставка под заказ. 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: Ukkusuri Название: Transportation Analytics in the Era of Big Data ISBN: 3319758616 ISBN-13(EAN): 9783319758619 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Preface.- Chapter 1. Beyond Geotagged Tweets: Exploring the Geolocalisation of Tweets for Transportation Applications.- Chapter 2. Social Media in Transportation Research and Promising Applications.- Chapter 3. Ground transportation big data analytics and third party validation - solutions for a new era of regulation and private sector innovation.- Chapter 4. A privacy-preserving urban traffic estimation system. - Chapter 5. Data, Methods, and Applications of Traffic Source Prediction. - Chapter 6. Analyzing the spatial and temporal characteristics of subway passenger flow based on smart card data.- Chapter 7. An Initial Evaluation of the Impact of Location Obfuscation Mechanisms on Geospatial Analysis.- Chapter 8. PETRA: The Personal Transport Advisor Platform and Services.- Chapter 9. Mobility Pattern Identification Based on Mobile Phone Data.
Автор: Finlay Steven Название: Predictive Analytics, Data Mining and Big Data ISBN: 1137379278 ISBN-13(EAN): 9781137379276 Издательство: Springer Рейтинг: Цена: 37260.00 T 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.
This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments.
Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people's imaginations as to what a fully connected world can offer.
Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions.
The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.
Автор: Satish V. Ukkusuri; Chao Yang Название: Transportation Analytics in the Era of Big Data ISBN: 3030093441 ISBN-13(EAN): 9783030093440 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents papers based on the presentations and discussions at the international workshop on Big Data Smart Transportation Analytics held July 16 and 17, 2016 at Tongji University in Shanghai and chaired by Professors Ukkusuri and Yang. The book is intended to explore a multidisciplinary perspective to big data science in urban transportation, motivated by three critical observations:The rapid advances in the observability of assets, platforms for matching supply and demand, thereby allowing sharing networks previously unimaginable.The nearly universal agreement that data from multiple sources, such as cell phones, social media, taxis and transit systems can allow an understanding of infrastructure systems that is critically important to both quality of life and successful economic competition at the global, national, regional, and local levels.There is presently a lack of unifying principles and methodologies that approach big data urban systems.The workshop brought together varied perspectives from engineering, computational scientists, state and central government, social scientists, physicists, and network science experts to develop a unifying set of research challenges and methodologies that are likely to impact infrastructure systems with a particular focus on transportation issues. The book deals with the emerging topic of data science for cities, a central topic in the last five years that is expected to become critical in academia, industry, and the government in the future. There is currently limited literature for researchers to know the opportunities and state of the art in this emerging area, so this book fills a gap by synthesizing the state of the art from various scholars and help identify new research directions for further study.
Автор: Galit Shmueli, Peter C. Bruce, Nitin R. Patel Название: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner ISBN: 1118729277 ISBN-13(EAN): 9781118729274 Издательство: Wiley Рейтинг: Цена: 118270.00 T Наличие на складе: Поставка под заказ. 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: Briffaut Название: E-enabled Operations Management ISBN: 1848218400 ISBN-13(EAN): 9781848218406 Издательство: Wiley Рейтинг: Цена: 146730.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Although the theory of operations management has been presented in many textbooks published in the last two decades, the subject of e-enabled operations management is rather short of easily accessible literature. The approach to operations management described in this book is unusual with respect to what is found in standard textbooks.
Автор: Shiro Uesugi Название: IT Enabled Services ISBN: 3709116880 ISBN-13(EAN): 9783709116883 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book opens up a new horizon with the application of Internet-based practices in business, government and daily life. Information Technology-Enabled Services works as a navigator for those who sail to the new horizon of service oriented economies
Автор: Sugumaran Название: E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life ISBN: 3319454072 ISBN-13(EAN): 9783319454078 Издательство: Springer Рейтинг: Цена: 46590.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the Workshop on E-Business (WeB 2015), held in Fort Worth, Texas, USA, on December 12, 2015. The theme of WeB 2015 was “Leveraging Service Computing and Big Data Analytics for E-Commerce”, and thus the workshop provided an interactive forum by bringing together researchers and practitioners from all over the world to explore the latest challenges of next-generation e-Business systems and the potential of service computing and big data analytics.The 11 full and 17 short papers, which were selected from 45 submissions to the workshop, addressed a broad coverage of technical, managerial, economic, and strategic issues related to e-business, with emphasis on service computing and big data analytics. They employed various IS research methods such as case study, survey, analytical modeling, experiments, computational models, and design science.
Автор: Stefan Michael Genennig Название: Realizing Digitization-Enabled Innovation ISBN: 3658287187 ISBN-13(EAN): 9783658287184 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Stefan Michael Genennig explores digitization-enabled innovation with a service systems perspective. Based on this grounding, he develops a method for the integration of digital technologies for service innovation and designs a tool for the development of digitization-enabled value propositions.
Автор: Mohapatra Название: Designing Knowledge Management-Enabled Business Strategies ISBN: 3319338935 ISBN-13(EAN): 9783319338934 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a practical approach to designing and implementing a Knowledge Management (KM) Strategy. The book explains how to design KM strategy so as to align business goals with KM objectives. The book also presents an approach for implementing KM strategy so as to make it sustainable. It covers all basic KM concepts, components of KM and the steps that are required for designing a KM strategy. As a result, the book can be used by beginners as well as practitioners.
Knowledge management is a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise's information assets. These assets may include databases, documents, policies, procedures, and previously un-captured expertise and experience in individual workers. Knowledge is considered to be the learning that results from experience and is embedded within individuals. Sometimes the knowledge is gained through critical thinking, watching others, and observing results of others. These observations then form a pattern which is converted in a ‘generic form’ to knowledge. This implies that knowledge can be formed only after data (which is generated through experience or observation) is grouped into information and then this information pattern is made generic wisdom. However, dissemination and acceptance of this knowledge becomes a key factor in knowledge management. The knowledge pyramid represents the usual concept of knowledge transformations, where data is transformed into information, and information is transformed into knowledge. Many organizations have struggled to manage knowledge and translate it into business benefits. This book is an attempt to show them how it can be done.
Автор: Antoniou, Constantinos Название: Mobility Patterns, Big Data and Transport Analytics ISBN: 0128129700 ISBN-13(EAN): 9780128129708 Издательство: Elsevier Science Рейтинг: Цена: 110030.00 T Наличие на складе: Поставка под заказ. Описание:
Transportation modelers and analysts face new opportunities and challenges in the study of mobility patterns and transportation systems, thanks to the advent of paradigm-shifting big data. Mobility Patterns, Big Data and Transport Analytics: Tools and Applications provides a guide to this new analytical framework related to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling.
Transportation systems analysis relies upon assumptions related to social, collective, personal, or disaggregate organization of desires expressed by the mobility of people or goods. Recent advances in information technology - such as available data from open sources, participation in media platforms, and sensor technologies - have created an environment of great change, and the potential for transportation structural reorganization. Mobility Patterns, Big Data and Transport Analytics: Tools and Applications features prominent international expert overview on these new analytical frameworks, applications, and concepts in mobility analysis and transportation systems.
The book covers in detail, mobility 'structural' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data's impact on mobility, and an introduction to the tools necessary to apply new techniques.
Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics
Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends
Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field
Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach
Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
