This book delves into the complex concept of data quality in the realm of information systems. The author approaches data quality from a process-oriented perspective, challenging the traditional product-oriented view. By introducing a formal model of an information system, the book provides a precise framework for analyzing and defining data quality dimensions. The author argues that data quality cannot be adequately conceptualized solely through product characteristics or user satisfaction. Instead, the focus should shift to the production process itself, where data quality defects can be identified and addressed. This process-centric approach offers a deeper understanding of the factors that contribute to data quality issues. With the aid of process constructs, the book defines five non-orthogonal dimensions of data quality: accuracy, completeness, relevance, timeliness, and interpretability. The analysis uncovers interdependencies among these dimensions, emphasizing the complexity of data quality assessment. This book challenges conventional wisdom on data quality and provides a transformative perspective for researchers and practitioners alike. It offers a rigorous foundation for data quality measurement and management, recognizing the significant impact data quality has on the effectiveness of information systems.
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Seller: Forgotten Books, London, United Kingdom
Paperback. Condition: New. Print on Demand. This book delves into the complex concept of data quality in the realm of information systems. The author approaches data quality from a process-oriented perspective, challenging the traditional product-oriented view. By introducing a formal model of an information system, the book provides a precise framework for analyzing and defining data quality dimensions. The author argues that data quality cannot be adequately conceptualized solely through product characteristics or user satisfaction. Instead, the focus should shift to the production process itself, where data quality defects can be identified and addressed. This process-centric approach offers a deeper understanding of the factors that contribute to data quality issues. With the aid of process constructs, the book defines five non-orthogonal dimensions of data quality: accuracy, completeness, relevance, timeliness, and interpretability. The analysis uncovers interdependencies among these dimensions, emphasizing the complexity of data quality assessment. This book challenges conventional wisdom on data quality and provides a transformative perspective for researchers and practitioners alike. It offers a rigorous foundation for data quality measurement and management, recognizing the significant impact data quality has on the effectiveness of information systems. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781334802362_0
Quantity: Over 20 available
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781334802362
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781334802362
Quantity: 15 available