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Handbook of Data Quality: Research and Practice - Shazia Sadiq
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Shazia Sadiq:
Handbook of Data Quality: Research and Practice - gebunden oder broschiert

ISBN: 3642362567

[SR: 3001249], Hardcover, [EAN: 9783642362569], Springer, Springer, Book, [PU: Springer], Springer, 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., 2648, Information Management, 2675, Management & Leadership, 3, Business & Money, 1000, Subjects, 283155, Books, 379382011, Data Modeling & Design, 549646, Databases & Big Data, 5, Computers & Technology, 1000, Subjects, 283155, Books, 10806617011, Storage & Retrieval, 377894011, Network Administration, 3652, Networking & Cloud Computing, 5, Computers & Technology, 1000, Subjects, 283155, Books, 10806628011, Enterprise Applications, 4053, Software, 5, Computers & Technology, 1000, Subjects, 283155, Books, 468220, Business & Finance, 491564, Accounting, 684243011, Banking, 491578, Business Communication, 684244011, Business Development, 491580, Business Ethics, 491506, Business Law, 491584, Economics, 684245011, Entrepreneurship, 491594, Finance, 491602, Human Resources, 684246011, International Business, 684247011, Investments & Securities, 684248011, Management, 491624, Marketing, 684249011, Real Estate, 684250011, Sales, 465600, New, Used & Rental Textbooks, 2349030011, Specialty Boutique, 283155, Books, 491306, Database Storage & Design, 468204, Computer Science, 465600, New, Used & Rental Textbooks, 2349030011, Specialty Boutique, 283155, Books

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Handbook of Data Quality: Research and Practice - Shazia Sadiq
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Shazia Sadiq:
Handbook of Data Quality: Research and Practice - gebunden oder broschiert

ISBN: 3642362567

[SR: 3001249], Hardcover, [EAN: 9783642362569], Springer, Springer, Book, [PU: Springer], Springer, 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., 2648, Information Management, 2675, Management & Leadership, 3, Business & Money, 1000, Subjects, 283155, Books, 379382011, Data Modeling & Design, 549646, Databases & Big Data, 5, Computers & Technology, 1000, Subjects, 283155, Books, 10806617011, Storage & Retrieval, 377894011, Network Administration, 3652, Networking & Cloud Computing, 5, Computers & Technology, 1000, Subjects, 283155, Books, 10806628011, Enterprise Applications, 4053, Software, 5, Computers & Technology, 1000, Subjects, 283155, Books, 468220, Business & Finance, 491564, Accounting, 684243011, Banking, 491578, Business Communication, 684244011, Business Development, 491580, Business Ethics, 491506, Business Law, 491584, Economics, 684245011, Entrepreneurship, 491594, Finance, 491602, Human Resources, 684246011, International Business, 684247011, Investments & Securities, 684248011, Management, 491624, Marketing, 684249011, Real Estate, 684250011, Sales, 465600, New, Used & Rental Textbooks, 2349030011, Specialty Boutique, 283155, Books, 491306, Database Storage & Design, 468204, Computer Science, 465600, New, Used & Rental Textbooks, 2349030011, Specialty Boutique, 283155, Books

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Handbook of Data Quality - Herausgegeben von Sadiq, Shazia
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Herausgegeben von Sadiq, Shazia:
Handbook of Data Quality - gebunden oder broschiert

2013, ISBN: 9783642362569

[ED: Hardcover], [PU: Springer, Berlin], The issue of data quality is as old as data itself. Further, the proliferation of quite diverse (e.g. in terms of structure or media type) shared or public data on the Web has increased the risk of poor data quality and false data aggregation. 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 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 IT tools and techniques related to record linkage, lineage and provenance, data uncertainty, and semantic 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. 2013. xii, 438 S. 92 SW-Abb. 235 mm Sofort lieferbar, DE, [SC: 0.00], Neuware, gewerbliches Angebot, offene Rechnung (Vorkasse vorbehalten)

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30, ISBN: 9783642362569

[ED: Buch], [PU: Springer-Verlag GmbH], Neuware - 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., DE, [SC: 0.00], Neuware, gewerbliches Angebot, FixedPrice, 420, [GW: 808g], offene Rechnung (Vorkasse vorbehalten), PayPal, Banküberweisung

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30, ISBN: 9783642362569

[ED: Buch], [PU: Springer-Verlag GmbH], Neuware - 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., DE, [SC: 0.00], Neuware, gewerbliches Angebot, 244x162x30 mm, 420, [GW: 808g], PayPal, Banküberweisung, Internationaler Versand

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Handbook of Data Quality
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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.

Detailangaben zum Buch - Handbook of Data Quality


EAN (ISBN-13): 9783642362569
ISBN (ISBN-10): 3642362567
Gebundene Ausgabe
Erscheinungsjahr: 2013
Herausgeber: Springer-Verlag GmbH
420 Seiten
Gewicht: 0,808 kg
Sprache: Englisch

Buch in der Datenbank seit 06.10.2009 09:39:18
Buch zuletzt gefunden am 15.11.2017 14:42:43
ISBN/EAN: 3642362567

ISBN - alternative Schreibweisen:
3-642-36256-7, 978-3-642-36256-9


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