Download or read book Improving data quality in relational databases written by Tennyson X. Chen and published by RTI Press. This book was released on 2011-05-19 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: The traditional vertical decomposition methods in relational database normalization fail to prevent common data anomalies. Although a database may be highly normalized, the quality of the data stored in this database may still deteriorate because of potential data anomalies. In this paper, we first discuss why practitioners need to further improve their databases after they apply the traditional normalization methods, because of the existence of functional entanglement, a phenomenon we defined. We outline two methods for identifying functional entanglements in a normalized database as the first step toward data quality improvement. We then analyze several practical methods for preventing common data anomalies by eliminating and restricting the effects of functional entanglements. The goal of this paper is to reveal shortcomings of the traditional database normalization methods with respect to the prevention of common data anomalies, and offer practitioners useful techniques for improving data quality.

Download or read book Improving Data Quality in Relational Databases written by Tennyson X. Chen and published by . This book was released on 2011 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Practitioner s Guide to Data Quality Improvement written by David Loshin and published by Elsevier. This book was released on 2010-11-22 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning.

Download or read book Improving Manifacturing Data Quality with Data Fusion and Advanced Algorithms for Improved Total Data Quality Management written by David Christoph Juriga and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining and predictive analytics in the sustainable-biomaterials industries is currently not feasible given the lack of organization and management of the database structures. The advent of artificial intelligence, data mining, robotics, etc., has become a standard for successful business endeavors and is known as the ‘Fourth Industrial Revolution’ or ‘Industry 4.0’ in Europe. Data quality improvement through real-time multi-layer data fusion across interconnected networks and statistical quality assessment may improve the usefulness of databases maintained by these industries. Relational databases with a high degree of quality may be the gateway for predictive modeling and enhanced business analytics. Data quality is a key issue in the sustainable bio-materials industry. Untreated data from multiple databases (e.g., sensor data and destructive test data) are generally not in the right structure to perform advanced analytics. Some inherent problems of data from sensors that are stored in data warehouses at millisecond intervals include missing values, duplicate records, sensor failure data (data out of feasible range), outliers, etc. These inherent problems of the untreated data represent information loss and mute predictive analytics. The goal of this data science focused research was to create a continuous real-time software algorithm for data cleaning that automatically aligns, fuses, and assesses data quality for missing fields and potential outliers. The program automatically reduces the variable size, imputes missing values, and predicts the destructive test data for every record in a database. Improved data quality was assessed using 10-fold cross-validation and the normalized root mean square error of prediction (NRMSEP) statistic. The impact of outliers and missing data were tested on a simulated dataset with 201 variations of outlier percentages ranging from 0-90% and missing data percentages ranging from 0-90%. The software program was also validated on a real dataset from the wood composites industry. One result of the research was that the number of sensors needed for accurate predictions are highly dependent on the correlation between independent variables and dependent variables. Overall, the data cleaning software program significantly decreased the NRMSEP ranging from 64% to 12% of quality control variables for key destructive test values (e.g., internal bond, water absorption and modulus of rupture).

Download or read book Data Quality written by Carlo Batini and published by Springer Science & Business Media. This book was released on 2006-09-27 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Principles of Database Management written by Wilfried Lemahieu and published by Cambridge University Press. This book was released on 2018-07-12 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

Download or read book Data Quality written by Rupa Mahanti and published by Quality Press. This book was released on 2019-03-18 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Good data is a source of myriad opportunities, while bad data is a tremendous burden. Companies that manage their data effectively are able to achieve a competitive advantage in the marketplace, while bad data, like cancer, can weaken and kill an organization. In this comprehensive book, Rupa Mahanti provides guidance on the different aspects of data quality with the aim to be able to improve data quality. Specifically, the book addresses: Causes of bad data quality, bad data quality impacts, and importance of data quality to justify the case for data quality Butterfly effect of data quality A detailed description of data quality dimensions and their measurement Data quality strategy approach Six Sigma - DMAIC approach to data quality Data quality management techniques Data quality in relation to data initiatives like data migration, MDM, data governance, etc. Data quality myths, challenges, and critical success factors Students, academicians, professionals, and researchers can all use the content in this book to further their knowledge and get guidance on their own specific projects. It balances technical details (for example, SQL statements, relational database components, data quality dimensions measurements) and higher-level qualitative discussions (cost of data quality, data quality strategy, data quality maturity, the case made for data quality, and so on) with case studies, illustrations, and real-world examples throughout. About the Author Rupa Mahanti, Ph.D. is a Business and Information Management consultant and has worked in different solution environments and industry sectors in the United States, United Kingdom, India, and Australia. She helps clients with activities such as business process mapping, information management, data quality, and strategy. Having a work experience (academic, industry, and research) of more than a decade and half, Rupa has guided a doctoral dissertation and published a large number of research articles. She is an associate editor with the journal Software Quality Professional and a reviewer for several international journals. "This is not the kind of book that you'll read one time and be done with. So scan it quickly the first time through to get an idea of its breadth. Then dig in on one topic of special importance to your work. Finally, use it as a reference to guide your next steps, learn details, and broaden your perspective." from the foreword by Thomas C. Redman, Ph.D., the Data Doc Dr. Mahanti provides a very detailed and thorough coverage of all aspects of data quality management that would suit all ranges of expertise from a beginner to an advanced practitioner. With plenty of examples, diagrams, etc. the book is easy to follow and will deepen your knowledge in the data domain. I will certainly keep this handy as my go-to reference. I can't imagine the level of effort and passion that Dr. Mahanti has put into this book that captures so much knowledge and experience for the benefit of the reader. I would highly recommend this book for its comprehensiveness, depth, and detail. A must-have for a data practitioner at any level. Clint D'Souza, CEO and Director, CDZM Consulting

Download or read book Information and Database Quality written by Mario G. Piattini and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a global and increasingly competitive market, where organizations are driven by information, the search for ways to transform data into true knowledge is critical to a business's success. Few companies, however, have effective methods of managing the quality of this information. Because quality is a multidimensional concept, its management must consider a wide variety of issues related to information and data quality. Information and Database Quality is a compilation of works from research and industry that examines these issues, covering both the organizational and technical aspects of information and data quality. Information and Database Quality is an excellent reference for both researchers and professionals involved in any aspect of information and database research.

Download or read book Data Management written by Richard T. Watson and published by . This book was released on 2004 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: PART I: THE MANAGERIAL PERSPECTIVE. Managing Data. Information. PART II: DATA MODELING AND SQL. The Single Entity. The One-to-Many Relationship. The Many-to-Many Relationship. One-to-One and Recursive Relationships. Data Modeling. Normalization and Other Data Modeling Methods. The Relational Model and Relational Algebra. SQL. PART III: DATABASE ARCHITECTURES AND IMPLEMENTATIONS. Data Structure and Storage. Data Processing Architectures. Object-Oriented Data Management. Spatial and Temporal Data Management. PART IV: ORGANIZATIONAL MEMORY TECHNOLOGIES. Organizational Intelligence Technologies. The Web and Data Management. XML: Managing Data Exchange. PART V: MANAGING ORGANIZTIONAL MEMORY. Data Integrity. Data Administration. U-Commerce and Data Management. Photo Credits. Index.

Download or read book Foundations of Data Quality Management written by Wenfei Fan and published by Springer Nature. This book was released on 2022-05-31 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data quality is one of the most important problems in data management. A database system typically aims to support the creation, maintenance, and use of large amount of data, focusing on the quantity of data. However, real-life data are often dirty: inconsistent, duplicated, inaccurate, incomplete, or stale. Dirty data in a database routinely generate misleading or biased analytical results and decisions, and lead to loss of revenues, credibility and customers. With this comes the need for data quality management. In contrast to traditional data management tasks, data quality management enables the detection and correction of errors in the data, syntactic or semantic, in order to improve the quality of the data and hence, add value to business processes. While data quality has been a longstanding problem for decades, the prevalent use of the Web has increased the risks, on an unprecedented scale, of creating and propagating dirty data. This monograph gives an overview of fundamental issues underlying central aspects of data quality, namely, data consistency, data deduplication, data accuracy, data currency, and information completeness. We promote a uniform logical framework for dealing with these issues, based on data quality rules. The text is organized into seven chapters, focusing on relational data. Chapter One introduces data quality issues. A conditional dependency theory is developed in Chapter Two, for capturing data inconsistencies. It is followed by practical techniques in Chapter 2b for discovering conditional dependencies, and for detecting inconsistencies and repairing data based on conditional dependencies. Matching dependencies are introduced in Chapter Three, as matching rules for data deduplication. A theory of relative information completeness is studied in Chapter Four, revising the classical Closed World Assumption and the Open World Assumption, to characterize incomplete information in the real world. A data currency model is presented in Chapter Five, to identify the current values of entities in a database and to answer queries with the current values, in the absence of reliable timestamps. Finally, interactions between these data quality issues are explored in Chapter Six. Important theoretical results and practical algorithms are covered, but formal proofs are omitted. The bibliographical notes contain pointers to papers in which the results were presented and proven, as well as references to materials for further reading. This text is intended for a seminar course at the graduate level. It is also to serve as a useful resource for researchers and practitioners who are interested in the study of data quality. The fundamental research on data quality draws on several areas, including mathematical logic, computational complexity and database theory. It has raised as many questions as it has answered, and is a rich source of questions and vitality. Table of Contents: Data Quality: An Overview / Conditional Dependencies / Cleaning Data with Conditional Dependencies / Data Deduplication / Information Completeness / Data Currency / Interactions between Data Quality Issues

Download or read book Data Quality Management with Semantic Technologies written by Christian Fürber and published by Springer. This book was released on 2015-12-11 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Christian Fürber investigates the useful application of semantic technologies for the area of data quality management. Based on a literature analysis of typical data quality problems and typical activities of data quality management processes, he develops the Semantic Data Quality Management framework as the major contribution of this thesis. The SDQM framework consists of three components that are evaluated in two different use cases. Moreover, this thesis compares the framework to conventional data quality software. Besides the framework, this thesis delivers important theoretical findings, namely a comprehensive typology of data quality problems, ten generic data requirement types, a requirement-centric data quality management process, and an analysis of related work.

Download or read book Dataspace The Final Frontier written by Alan Sexton and published by Springer. This book was released on 2009-06-30 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 26th British National Conference on Databases, BNCOD 26, held in Birmingham, UK, in July 2009. The 12 revised full papers, 2 short papers and 5 poster papers presented together with 2 keynote talks, 2 tutorial papers and summaries of 3 co-located workshops were carefully reviewed and selected from 33 submissions. The papers are organized in topical sections on data integration, warehousing and privacy; alternative data models; querying; and path queries and XML;data mining and privacy, data integration, stream and event data processing, and query processing and optimisation.

Download or read book Understanding Information Retrieval Systems written by Marcia J. Bates and published by CRC Press. This book was released on 2011-12-20 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to be effective for their users, information retrieval (IR) systems should be adapted to the specific needs of particular environments. The huge and growing array of types of information retrieval systems in use today is on display in Understanding Information Retrieval Systems: Management, Types, and Standards, which addresses over 20 types of IR systems. These various system types, in turn, present both technical and management challenges, which are also addressed in this volume. In order to be interoperable in a networked environment, IR systems must be able to use various types of technical standards, a number of which are described in this book—often by their original developers. The book covers the full context of operational IR systems, addressing not only the systems themselves but also human user search behaviors, user-centered design, and management and policy issues. In addition to theory and practice of IR system design, the book covers Web standards and protocols, the Semantic Web, XML information retrieval, Web social mining, search engine optimization, specialized museum and library online access, records compliance and risk management, information storage technology, geographic information systems, and data transmission protocols. Emphasis is given to information systems that operate on relatively unstructured data, such as text, images, and music. The book is organized into four parts: Part I supplies a broad-level introduction to information systems and information retrieval systems Part II examines key management issues and elaborates on the decision process around likely information system solutions Part III illustrates the range of information retrieval systems in use today discussing the technical, operational, and administrative issues for each type Part IV discusses the most important organizational and technical standards needed for successful information retrieval This volume brings together authoritative articles on the different types of information systems and how to manage real-world demands such as digital asset management, network management, digital content licensing, data quality, and information system failures. It explains how to design systems to address human characteristics and considers key policy and ethical issues such as piracy and preservation. Focusing on web–based systems, the chapters in this book provide an excellent starting point for developing and managing your own IR systems.

Download or read book InfoWorld written by and published by . This book was released on 2005-03-14 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects.

Download or read book Data Quality and Record Linkage Techniques written by Thomas N. Herzog and published by Springer Science & Business Media. This book was released on 2007-05-23 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a practical understanding of issues involved in improving data quality through editing, imputation, and record linkage. The first part of the book deals with methods and models, focusing on the Fellegi-Holt edit-imputation model, the Little-Rubin multiple-imputation scheme, and the Fellegi-Sunter record linkage model. The second part presents case studies in which these techniques are applied in a variety of areas, including mortgage guarantee insurance, medical, biomedical, highway safety, and social insurance as well as the construction of list frames and administrative lists. This book offers a mixture of practical advice, mathematical rigor, management insight and philosophy.

Download or read book Computational Science and Its Applications ICCSA 2011 written by Beniamino Murgante and published by Springer. This book was released on 2011-06-17 with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: The five-volume set LNCS 6782 - 6786 constitutes the refereed proceedings of the International Conference on Computational Science and Its Applications, ICCSA 2011, held in Santander, Spain, in June 2011. The five volumes contain papers presenting a wealth of original research results in the field of computational science, from foundational issues in computer science and mathematics to advanced applications in virtually all sciences making use of computational techniques. The topics of the fully refereed papers are structured according to the five major conference themes: geographical analysis, urban modeling, spatial statistics; cities, technologies and planning; computational geometry and applications; computer aided modeling, simulation, and analysis; and mobile communications.

Download or read book Nelson Textbook of Pediatrics E Book written by Robert M. Kliegman and published by Elsevier Health Sciences. This book was released on 2011-06-01 with total page 2680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nelson Textbook of Pediatrics has been the world’s most trusted pediatrics resource for nearly 75 years. Drs. Robert Kliegman, Bonita Stanton, Richard Behrman, and two new editors—Drs. Joseph St. Geme and Nina Schor—continue to provide the most authoritative coverage of the best approaches to care. This streamlined new edition covers the latest on genetics, neurology, infectious disease, melamine poisoning, sexual identity and adolescent homosexuality, psychosis associated with epilepsy, and more. Understand the principles of therapy and which drugs and dosages to prescribe for every disease. Locate key content easily and identify clinical conditions quickly thanks to a full-color design and full-color photographs. Stay current on recent developments and hot topics such as melamine poisoning, long-term mechanical ventilation in the acutely ill child, sexual identity and adolescent homosexuality, age-specific behavior disturbances, and psychosis associated with epilepsy. Tap into substantially enhanced content with world-leading clinical and research expertise from two new editors—Joseph St. Geme, III, MD and Nina Schor, MD—who contribute on the key subspecialties, including pediatric infectious disease and pediatric neurology. Manage the transition to adult healthcare for children with chronic diseases through discussions of the overall health needs of patients with congenital heart defects, diabetes, and cystic fibrosis. Recognize, diagnose, and manage genetic conditions more effectively using an expanded section that covers these diseases, disorders, and syndromes extensively. Find information on chronic and common dermatologic problems more easily with a more intuitive reorganization of the section.