Quality Information And Knowledge
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| Author | : Martin J. Eppler |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 312 |
| Release | : 2013-06-05 |
| Genre | : Business & Economics |
| ISBN | : 3540247823 |
What makes information useful? This seemingly simple and yet intriguing and complicated question is discussed in this book. It examines ways in which the quality of information can be improved in knowledge-intensive processes (such as on-line communication, strategy, product development, or consulting). Based on existing information quality literature, the book proposes a conceptual framework to manage information quality for knowledge-based content. It presents four proven principles to apply the framework to a variety of information products. Five in-depth company case studies show how information quality can be managed systematically. The book uses frequent diagrams and tables, as well as diagnostic questions and summary boxes to make its content actionable.
| Author | : Kuan-Tsae Huang |
| Publisher | : Prentice Hall |
| Total Pages | : 0 |
| Release | : 1999 |
| Genre | : Business |
| ISBN | : 9780130101419 |
| Author | : David Loshin |
| Publisher | : Morgan Kaufmann |
| Total Pages | : 516 |
| Release | : 2001 |
| Genre | : Business & Economics |
| ISBN | : 9780124558403 |
This volume presents a methodology for defining, measuring and improving data quality. It lays out an economic framework for understanding the value of data quality, then outlines data quality rules and domain- and mapping-based approaches to consolidating enterprise knowledge.
| Author | : Ron S. Kenett |
| Publisher | : John Wiley & Sons |
| Total Pages | : 381 |
| Release | : 2016-12-19 |
| Genre | : Mathematics |
| ISBN | : 1118874447 |
Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management. This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website. This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.
| Author | : Luciano Floridi |
| Publisher | : Springer |
| Total Pages | : 315 |
| Release | : 2014-08-01 |
| Genre | : Philosophy |
| ISBN | : 3319071211 |
This work fulfills the need for a conceptual and technical framework to improve understanding of Information Quality (IQ) and Information Quality standards. The meaning and practical implementation of IQ are addressed, as it is relevant to any field where there is a need to handle data and issues such as accessibility, accuracy, completeness, currency, integrity, reliability, timeliness, usability, the role of metrics and so forth are all a part of Information Quality. In order to support the cross-fertilization of theory and practice, the latest research is presented in this book. The perspectives of experts from beyond the origins of IQ in computer science are included: library and information science practitioners and academics, philosophers of information, of engineering and technology, and of science are all contributors to this volume. The chapters in this volume are based on the work of a collaborative research project involving the Arts and Humanities Research Council and Google and led by Professor Luciano Floridi, University of Oxford. This work will be of interest to anyone handling data, including those from commercial, public, governmental and academic organizations. The expert editors’ contributions introduce issues of interest to scientists, database curators and philosophers, even though the issues may be disguised in the language and examples common to a different discipline.
| Author | : Carlo Batini |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 276 |
| Release | : 2006-09-27 |
| Genre | : Computers |
| ISBN | : 3540331735 |
Poor data quality can seriously hinder or damage the efficiency and effectiveness of organizations and businesses. The growing awareness of such repercussions has led to major public initiatives like the "Data Quality Act" in the USA and the "European 2003/98" directive of the European Parliament. Batini and Scannapieco present a comprehensive and systematic introduction to the wide set of issues related to data quality. They start with a detailed description of different data quality dimensions, like accuracy, completeness, and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change, like stable, long-term, and frequently changing data. The book's extensive description of techniques and methodologies from core data quality research as well as from related fields like data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art. The presentation is completed by a short description and critical comparison of tools and practical methodologies, which will help readers to resolve their own quality problems. This book is an ideal combination of the soundness of theoretical foundations and the applicability of practical approaches. It is ideally suited for everyone – researchers, students, or professionals – interested in a comprehensive overview of data quality issues. In addition, it will serve as the basis for an introductory course or for self-study on this topic.
| Author | : Thomas H. Davenport |
| Publisher | : Harvard Business Press |
| Total Pages | : 216 |
| Release | : 2000-04-26 |
| Genre | : Business & Economics |
| ISBN | : 1422160688 |
This influential book establishes the enduring vocabulary and concepts in the burgeoning field of knowledge management. It serves as the hands-on resource of choice for companies that recognize knowledge as the only sustainable source of competitive advantage going forward. Drawing from their work with more than thirty knowledge-rich firms, Davenport and Prusak--experienced consultants with a track record of success--examine how all types of companies can effectively understand, analyze, measure, and manage their intellectual assets, turning corporate wisdom into market value. They categorize knowledge work into four sequential activities--accessing, generating, embedding, and transferring--and look at the key skills, techniques, and processes of each. While they present a practical approach to cataloging and storing knowledge so that employees can easily leverage it throughout the firm, the authors caution readers on the limits of communications and information technology in managing intellectual capital.
| Author | : Yeoh, William |
| Publisher | : IGI Global |
| Total Pages | : 478 |
| Release | : 2013-12-31 |
| Genre | : Business & Economics |
| ISBN | : 1466648937 |
Business intelligence initiatives have been dominating the technology priority list of many organizations. However, the lack of effective information quality and governance strategies and policies has been meeting these initiatives with some challenges. Information Quality and Governance for Business Intelligence presents the latest exchange of academic research on all aspects of practicing and managing information using a multidisciplinary approach that examines its quality for organizational growth. This book is an essential reference tool for researchers, practitioners, and university students specializing in business intelligence, information quality, and information systems.
| Author | : Michelle Carey |
| Publisher | : Pearson Education |
| Total Pages | : 612 |
| Release | : 2014 |
| Genre | : Computers |
| ISBN | : 0133118975 |
Drawing on IBM's unsurpassed technical communications experience, readers discover today's best practices for meeting nine quality characteristics: accuracy, clarity, completeness, concreteness, organization, retrievability, style, task orientation, and visual effectiveness. Packed with guidelines, checklists, and before-and-after examples, Developing Quality Technical Information, Third Edition is an indispensable resource for the future of technical communication.
| Author | : Gyamfi, Albert |
| Publisher | : IGI Global |
| Total Pages | : 275 |
| Release | : 2021-06-18 |
| Genre | : Business & Economics |
| ISBN | : 1799867943 |
Knowledge management has always been about the process of creating, sharing, using, and applying knowledge within and between organizations. Before the advent of information systems, knowledge management processes were manual or offline. However, the emergence and eventual evolution of information systems created the possibility for the gradual but slow automation of knowledge management processes. These digital technologies enable data capture, data storage, data mining, data analytics, and data visualization. The value provided by such technologies is enhanced and distributed to organizations as well as customers using the digital technologies that enable interconnectivity. Today, the fine line between the technologies enabling the technology-driven external pressures and data-driven internal organizational pressures is blurred. Therefore, how technologies are combined to facilitate knowledge management processes is becoming less standardized. This results in the question of how the current advancement in digital technologies affects knowledge management processes both within and outside organizations. Digital Technology Advancements in Knowledge Management addresses how various new and emerging digital technologies can support knowledge management processes within organizations or outside organizations. Case studies and practical tips based on research on the emerging possibilities for knowledge management using these technologies is discussed within the chapters of this book. It both builds on the available literature in the field of knowledge management while providing for further research opportunities in this dynamic field. This book highlights topics such as human-robot interaction, big data analytics, software development, keyword extraction, and artificial intelligence and is ideal for technology developers, academics, researchers, managers, practitioners, stakeholders, and students who are interested in the adoption and implementation of new digital technologies for knowledge creation, sharing, aggregation, and storage.
