Handbook On Data Management In Information Systems
Download Handbook On Data Management In Information Systems PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Handbook On Data Management In Information Systems book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Handbook on Data Management in Information Systems
Author: Jacek Blazewicz
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
This book is the sixth of a running series of volumes dedicated to selected topics of information theory and practice. The objective of the series is to pro vide a reference source for problem solvers in business, industry, government, and professional researchers and gradute students. The first volume, Handbook on Architecture of Information Systems, presents a balanced number of contributions from academia and practition ers. The structure of the material follows a differentiation between model ing languages, tools and methodologies. The second volume, Handbook on Electronic Commerce, examines electronic commerce storefront, on-line busi ness, consumer interface, business-to-business networking, digital payment, legal issues, information product development and electronic business mod els. The third volume, Handbook on Parallel and Distributed Processing, presents basic concepts, methods, and recent developments in the field of parallel and distributed processing as well as some important aplications of parallel and distributed computing. In particular, the book examines such fundamental issues in the above area as languages for parallel processing, parallel operating systems, architecture of parallel and distributed systems, parallel database and multimedia systems, networking aspects of parallel and distributed systems, efficiency of parallel algorithms. The fourth volume on Information Technologies for Education and Training is· devoted to a pre sentation of current and future research and applications in the field of ed ucational technology. The fifth double volume on Knowledge Management contains an extensive, fundamental coverage of the knowledge management field.
Information Systems Management in the Big Data Era
This timely text/reference explores the business and technical issues involved in the management of information systems in the era of big data and beyond. Topics and features: presents review questions and discussion topics in each chapter for classroom group work and individual research assignments; discusses the potential use of a variety of big data tools and techniques in a business environment, explaining how these can fit within an information systems strategy; reviews existing theories and practices in information systems, and explores their continued relevance in the era of big data; describes the key technologies involved in information systems in general and big data in particular, placing these technologies in an historic context; suggests areas for further research in this fast moving domain; equips readers with an understanding of the important aspects of a data scientist’s job; provides hands-on experience to further assist in the understanding of the technologies involved.
Handbook of Data Quality
Author: Shazia Sadiq
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-08-13
The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects. Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors. Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches.