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Principles Of Data Integration

Author: AnHai Doan
Publisher: Elsevier
ISBN: 0123914795
Size: 36.51 MB
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How do you approach answering queries when your data is stored in multiple databases that were designed independently by different people? This is first comprehensive book on data integration and is written by three of the most respected experts in the field. This book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. Data integration is the problem of answering queries that span multiple data sources (e.g., databases, web pages). Data integration problems surface in multiple contexts, including enterprise information integration, query processing on the Web, coordination between government agencies and collaboration between scientists. In some cases, data integration is the key bottleneck to making progress in a field. The authors provide a working knowledge of data integration concepts and techniques, giving you the tools you need to develop a complete and concise package of algorithms and applications. Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand Enables you to build your own algorithms and implement your own data integration applications

Attribution Principles For Data Integration

Author: Thomas Yupoo Lee
Publisher:
ISBN:
Size: 46.83 MB
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(cont.) The policy perspective encompasses not only what and where but also integration architectures and the relationships between data providers and users. Information technologies separate the processes and products of data gathering from data selection and presentation. Where the latter is addressed by copyright, the former is not addressed at all. Based upon two traditional, legal-economic frameworks, the asymmetric Prisoner's Dilemma and Entitlement Theory, we argue for a policy of misappropriation to support integration and attribution for data.

Data Integration Blueprint And Modeling

Author: Anthony David Giordano
Publisher: Pearson Education
ISBN: 0137085281
Size: 45.87 MB
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Making Data Integration Work: How to Systematically Reduce Cost, Improve Quality, and Enhance Effectiveness Today’s enterprises are investing massive resources in data integration. Many possess thousands of point-to-point data integration applications that are costly, undocumented, and difficult to maintain. Data integration now accounts for a major part of the expense and risk of typical data warehousing and business intelligence projects--and, as businesses increasingly rely on analytics, the need for a blueprint for data integration is increasing now more than ever. This book presents the solution: a clear, consistent approach to defining, designing, and building data integration components to reduce cost, simplify management, enhance quality, and improve effectiveness. Leading IBM data management expert Tony Giordano brings together best practices for architecture, design, and methodology, and shows how to do the disciplined work of getting data integration right. Mr. Giordano begins with an overview of the “patterns” of data integration, showing how to build blueprints that smoothly handle both operational and analytic data integration. Next, he walks through the entire project lifecycle, explaining each phase, activity, task, and deliverable through a complete case study. Finally, he shows how to integrate data integration with other information management disciplines, from data governance to metadata. The book’s appendices bring together key principles, detailed models, and a complete data integration glossary. Coverage includes Implementing repeatable, efficient, and well-documented processes for integrating data Lowering costs and improving quality by eliminating unnecessary or duplicative data integrations Managing the high levels of complexity associated with integrating business and technical data Using intuitive graphical design techniques for more effective process and data integration modeling Building end-to-end data integration applications that bring together many complex data sources

Data Integration In The Life Sciences

Author: Erhard Rahm
Publisher: Springer Science & Business Media
ISBN: 3540213007
Size: 65.80 MB
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This book constitutes the refereed proceedings of the First International Workshop on Data Integration in the Life Sciences, DILS 2004, held in Leipzig, Germany, in March 2004. The 13 revised full papers and 2 revised short papers presented were carefully reviewed and selected from many submissions. The papers are organized in topical sections on scientific and clinical workflows, ontologies and taxonomies, indexing and clustering, integration tools and systems, and integration techniques.

Principles Of Distributed Database Systems

Author: M. Tamer Özsu
Publisher: Springer Science & Business Media
ISBN: 9781441988348
Size: 13.13 MB
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This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced a renewal of interest in distributed and parallel data management, while, at the same time, requiring a rethinking of some of the traditional techniques. This book covers the breadth and depth of this re-emerging field. The coverage consists of two parts. The first part discusses the fundamental principles of distributed data management and includes distribution design, data integration, distributed query processing and optimization, distributed transaction management, and replication. The second part focuses on more advanced topics and includes discussion of parallel database systems, distributed object management, peer-to-peer data management, web data management, data stream systems, and cloud computing. New in this Edition: • New chapters, covering database replication, database integration, multidatabase query processing, peer-to-peer data management, and web data management. • Coverage of emerging topics such as data streams and cloud computing • Extensive revisions and updates based on years of class testing and feedback Ancillary teaching materials are available.

Principles Of Big Data

Author: Jules J. Berman
Publisher: Newnes
ISBN: 0124047246
Size: 31.56 MB
Format: PDF, ePub
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Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. Learn general methods for specifying Big Data in a way that is understandable to humans and to computers Avoid the pitfalls in Big Data design and analysis Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources

Principles Of Case Tool Integration

Author: Alan W. Brown
Publisher: Oxford University Press
ISBN: 9780195357417
Size: 32.28 MB
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Computer Aided Software Engineering (CASE) tools typically support individual users in the automation of a set of tasks within a software development process. Such tools have helped organizations in their efforts to develop better software within budget and time constraints. However, many organizations are failing to take full advantage of CASE technology as they struggle to make coordinated use of collections of tools, often obtained at different times from different vendors. This book provides an in-depth analysis of the CASE tool integration problem, and describes practical approaches that can be used with current CASE technology to help your organization take greater advantage of integrated CASE.

Principles Of Data Wrangling

Author: Tye Rattenbury
Publisher: "O'Reilly Media, Inc."
ISBN: 1491938897
Size: 11.25 MB
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A key task that any aspiring data-driven organization needs to learn is data wrangling, the process of converting raw data into something truly useful. This practical guide provides business analysts with an overview of various data wrangling techniques and tools, and puts the practice of data wrangling into context by asking, "What are you trying to do and why?" Wrangling data consumes roughly 50-80% of an analyst's time before any kind of analysis is possible. Written by key executives at Trifacta, this book walks you through the wrangling process by exploring several factors--time, granularity, scope, and structure--that you need to consider as you begin to work with data. You'll learn a shared language and a comprehensive understanding of data wrangling, with an emphasis on recent agile analytic processes used by many of today's data-driven organizations. Appreciate the importance--and the satisfaction--of wrangling data the right way. Understand what kind of data is available Choose which data to use and at what level of detail Meaningfully combine multiple sources of data Decide how to distill the results to a size and shape that can drive downstream analysis

Principles Of Database Management

Author: Wilfried Lemahieu
Publisher: Cambridge University Press
ISBN: 1107186129
Size: 79.60 MB
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Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.