Deptinfo Cnam
Download Deptinfo Cnam PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Deptinfo Cnam 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.
Enterprise Information Systems
This book constitutes revised selected papers from the 18th International Conference on Enterprise Information Systems, ICEIS 2016, held in Rome, Italy, in April 2016. The 23 papers presented in this volume were carefully reviewed and selected from a total of 257 submissions to ICEIS 2016. The volume also contains one invited talk in full paper length. The papers selected to be included in this book contribute to the understanding of relevant trends of current research on enterprise information systems, including issues with regard to enterprise engineering, heterogeneous systems, security, software engineering, systems integration, business process management, human factors and affective computing, ubiquitous computing, social computing, knowledge management, and artificial intelligence.
Management of Data Quality in Enterprise Resource Planning Systems
Originally presented as the author's thesis (doctoral)--Universiteat Bern, 2010.
Data Quality
Author: Carlo Batini
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-09-27
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.