Описание: This book aims to apply data mining and analytic techniques to past workplace accident data to discover patterns that facilitate the development of innovative models and strategies.
Автор: Anandakumar Haldorai, Arulmurugan Ramu Название: Cognitive Social Mining Applications in Data Analytics and Forensics ISBN: 1522575227 ISBN-13(EAN): 9781522575221 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28413.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data.Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.
Автор: Venkata M. V. Gunturi; Shashi Shekhar Название: Spatio-Temporal Graph Data Analytics ISBN: 3319884867 ISBN-13(EAN): 9783319884868 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book highlights some of the unique aspects of spatio-temporal graph data from the perspectives of modeling and developing scalable algorithms.
Описание: Use data, analytics and metrics to make better HR decisions for your business.
Автор: Parul Gandhi; Surbhi Bhatia; Kapil Dev; Название: Data driven decision making using analytics ISBN: 1032058277 ISBN-13(EAN): 9781032058276 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining.Features:Covers descriptive statistics with respect to predictive analytics and business analytics.Discusses different data analytics platforms for real-time applications.Explain SMART business models.Includes algorithms in data sciences alongwith automated methods and models.Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics.This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.
Автор: Lowell Fryman Название: The Data and Analytics Playbook ISBN: 0128023074 ISBN-13(EAN): 9780128023075 Издательство: Elsevier Science Рейтинг: Цена: 7409.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration.
The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it.
In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization.
Автор: Williams, Steve Название: Business Intelligence Strategy and Big Data Analytics ISBN: 0128091983 ISBN-13(EAN): 9780128091982 Издательство: Elsevier Science Рейтинг: Цена: 5388.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges.
In recent years, terms like "big data" and "big data analytics" have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both.
Provides ideas for improving the business performance of one's company or business functions
Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies
Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans
Название: Data Analytics Applications In Law ISBN: 149876665X ISBN-13(EAN): 9781498766654 Издательство: Taylor&Francis Рейтинг: Цена: 12707.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: For increasingly data-savvy clients, lawyers can no longer give "it depends" answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer informed by the most relevant information required to answer their questions.
Data-Driven Law: Data Analytics and the New Legal Services helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as:
Mining legal data
Computational law
Uncovering bias through the use of Big Data
Quantifying the quality of legal services
Data mining and decision-making
Contract analytics and contract standards
In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable.
Data-driven decision-making requires firms to think differently about their workflow. Most firms warehouse their files, never to be seen again after the matter closes. Running a data-driven firm requires lawyers and their teams to treat information about the work as part of the service, and to collect, standardize, and analyze matter data from cradle to grave. More than anything, using data in a law practice requires a different mindset about the value of this information. This book helps legal professionals to develop this data-driven mindset.
Описание: Apply the tools and techniques of text analytics with ease and add value to your company by understanding its key approaches and the business reality behind them.
Название: Data analytics and psychometrics ISBN: 1641133260 ISBN-13(EAN): 9781641133265 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7623.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The general theme of this book is to encourage the use of relevant methodology in data mining which is or could be applied to the interplay of education, statistics and computer science to solve psychometric issues and challenges in the new generation of assessments. In addition to item response data, other data collected in the process of assessment and learning will be utilized to help solve psychometric challenges and facilitate learning and other educational applications. Process data include those collected or available for collection during the process of assessment and instructional phase such as responding sequence data, log files, the use of help features, the content of web searches, etc. Some book chapters present the general exploration of process data in large -scale assessment. Further, other chapters also address how to integrate psychometrics and learning analytics in assessment and survey, how to use data mining techniques for security and cheating detection, how to use more assessment results to facilitate student’s learning and guide teacher’s instructional efforts. The book includes both theoretical and methodological presentations that might guide the future in this area, as well as illustrations of efforts to implement big data analytics that might be instructive to those in the field of learning and psychometrics. The context of the effort is diverse, including K-12, higher education, financial planning, and survey utilization. It is hoped that readers can learn from different disciplines, especially those who are specialized in assessment, would be critical to expand the ideas of what we can do with data analytics for informing assessment practices.
Автор: David Niemi, Roy D. Pea, Bror Saxberg, Richard E. Clark Название: Learning Analytics in Education ISBN: 1641133694 ISBN-13(EAN): 9781641133692 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7623.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a comprehensive introduction by an extraordinary range of experts to the recent and rapidly developing field of learning analytics. Some of the finest current thinkers about ways to interpret and benefit from the increasing amount of evidence from learners’ experiences have taken time to explain their methods, describe examples, and point out new underpinnings for the field. Together, they show how this new field has the potential to dramatically increase learner success through deeper understanding of the academic, social-emotional, motivational, identity and meta-cognitive context each learner uniquely brings. Learning analytics is much more than “analyzing learning data”—it is about deeply understanding what learning activities work well, for whom, and when.Learning Analytics in Education provides an essential framework, as well as guidance and examples, for a wide range of professionals interested in the future of learning. If you are already involved in learning analytics, or otherwise trying to use an increasing density of evidence to understand learners’ progress, these leading thinkers in the field may give you new insights. If you are engaged in teaching at any level, or training future teachers/faculty for this new, increasingly technology-enhanced learning world, and want some sense of the potential opportunities (and pitfalls) of what technology can bring to your teaching and students, these forward-thinking leaders can spark your imagination. If you are involved in research around uses of technology, improving learning measurements, better ways to use evidence to improve learning, or in more deeply understanding human learning itself, you will find additional ideas and insights from some of the best thinkers in the field here. If you are involved in making administrative or policy decisions about learning, you will find new ideas (and dilemmas) coming your way from inevitable changes in how we design and deliver instruction, how we measure the outcomes, and how we provide feedback to students, teachers, developers, administrators, and policy-makers. For all these players, the trick will be to get the most out of all the new developments to efficiently and effectively improve learning performance, without getting distracted by “shiny” technologies that are disconnected from how human learning and development actually work.
Автор: David Niemi, Roy D. Pea, Bror Saxberg, Richard E. Clark Название: Learning Analytics in Education ISBN: 1641133708 ISBN-13(EAN): 9781641133708 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14137.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides a comprehensive introduction by a range of experts to the recent and rapidly developing field of learning analytics. Contributors show how this new field has the potential to increase learner success through understanding of the academic, social-emotional, motivational, identity and meta-cognitive context each learner brings.
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