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9781332247592: Where Does the Data Come From: Managing Data Integration With Source Tagging Capabilities (Classic Reprint)

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Excerpt from Where Does the Data Come From: Managing Data Integration With Source Tagging Capabilities

Abstract Many important Management Support Systems require access to and seamless integration of multiple heterogeneous database systems. This paper studies heterogeneous database systems from the source perspective. It aims at addressing issues such as the following. (1) Where is the data from? (2) Which intermediate sources were used to arrive at that data? Specifically, it presents a polygen model for resolving these data source and intermediate source problems. The polygen model provides a precise characterization of the source tagging problem and a solution including a polygen algebra, a data - driven query translation mechanism, and the necessary and sufficient condition for source tagging. This model has been developed as a direct extension of the relational model to the multiple database setting with source tagging capabilities, thus it enjoys all of the strengths of the traditional relational model. Source knowledge is important for many reasons. It enables users to apply their own judgment to the credibility of the information. It enables users to rationalize and reconcile data inconsistencies. It enables system designers to develop access charge systems. It enables an application user to adjust data. And it enables a system to interpret data semantics more accurately. In sum, source tagging capabilities should be a required functionality for future heterogeneous database systems.

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This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

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Y. Richard Wang
Publicado por Forgotten Books, 2018
ISBN 10: 1332247598 ISBN 13: 9781332247592
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781332247592

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Y. Richard Wang
Publicado por Forgotten Books, 2018
ISBN 10: 1332247598 ISBN 13: 9781332247592
Nuevo PAP

Librería: PBShop.store UK, Fairford, GLOS, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781332247592

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Y. Richard Wang, Stuart E. Madnick
Publicado por Forgotten Books, 2018
ISBN 10: 1332247598 ISBN 13: 9781332247592
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Librería: Forgotten Books, London, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Paperback. Condición: New. Print on Demand. This book delves into the integration of information systems from the angle of their data sources, a field that has garnered scant attention until now. It primarily tackles two major challenges in the field: 1) tracking the origin of data; and 2) understanding which intermediate data sources contributed to the data's arrival at its final destination. The author presents a 'polygen model' and a solution for resolving these challenges that is compatible with existing relational database systems, a legacy technology that currently dominates the database market. With this, the author makes a substantial step towards removing the obstacles that persist in combining data from disparate sources. 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. Nº de ref. del artículo: 9781332247592_0

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