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Principles of Data Integration

Principles of Data Integration
A Book

by AnHai Doan,Alon Halevy,Zachary Ives

  • Publisher : Elsevier
  • Release : 2012-06-25
  • Pages : 520
  • ISBN : 0123914795
  • Language : En, Es, Fr & De
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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

Principles of Data Integration

Principles of Data Integration
A Book

by AnHai Doan,Alon Halevy,Zachary G. Ives

  • Publisher : Elsevier
  • Release : 2012
  • Pages : 497
  • ISBN : 0124160441
  • Language : En, Es, Fr & De
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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 *Companion website with numerous project-based exercises and solutions and slides. Links to commercially available software allowing readers to build their own algorithms and implement their own data integration applications. Facebook page for reader input during and after publication.

Attribution Principles for Data Integration

Attribution Principles for Data Integration
Technology and Policy Perspectives

by Thomas Yupoo Lee,Massachusetts Institute of Technology. Technology, Management, and Policy Program

  • Publisher : Unknown Publisher
  • Release : 2002
  • Pages : 250
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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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

Data Integration Blueprint and Modeling
Techniques for a Scalable and Sustainable Architecture

by Anthony David Giordano

  • Publisher : Pearson Education
  • Release : 2010-12-27
  • Pages : 500
  • ISBN : 0137085281
  • Language : En, Es, Fr & De
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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

Big Data Integration

Big Data Integration
A Book

by Xin Luna Dong,Divesh Srivastava

  • Publisher : Morgan & Claypool Publishers
  • Release : 2015-02-01
  • Pages : 198
  • ISBN : 1627052240
  • Language : En, Es, Fr & De
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The big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions of volume, velocity, variety, and veracity. First, not only can data sources contain a huge volume of data, but also the number of data sources is now in the millions. Second, because of the rate at which newly collected data are made available, many of the data sources are very dynamic, and the number of data sources is also rapidly exploding. Third, data sources are extremely heterogeneous in their structure and content, exhibiting considerable variety even for substantially similar entities. Fourth, the data sources are of widely differing qualities, with significant differences in the coverage, accuracy and timeliness of data provided. This book explores the progress that has been made by the data integration community on the topics of schema alignment, record linkage and data fusion in addressing these novel challenges faced by big data integration. Each of these topics is covered in a systematic way: first starting with a quick tour of the topic in the context of traditional data integration, followed by a detailed, example-driven exposition of recent innovative techniques that have been proposed to address the BDI challenges of volume, velocity, variety, and veracity. Finally, it presents merging topics and opportunities that are specific to BDI, identifying promising directions for the data integration community.

Data Integration in the Life Sciences

Data Integration in the Life Sciences
First International Workshop, DILS 2004, Leipzig, Germany, March 25-26, 2004, Proceedings

by Germany) Dils 200 2004 (Leipzig,International Workshop on Data Integration in the Life Sciences (1 : 2004 : Leipzig)

  • Publisher : Springer Science & Business Media
  • Release : 2004-03-18
  • Pages : 219
  • ISBN : 3540213007
  • Language : En, Es, Fr & De
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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 Data Wrangling

Principles of Data Wrangling
Practical Techniques for Data Preparation

by Tye Rattenbury

  • Publisher : "O'Reilly Media, Inc."
  • Release : 2017-06-29
  • Pages : 129
  • ISBN : 1491938897
  • Language : En, Es, Fr & De
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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

AI and Big Data’s Potential for Disruptive Innovation

AI and Big Data’s Potential for Disruptive Innovation
A Book

by Strydom, Moses,Buckley, Sheryl

  • Publisher : IGI Global
  • Release : 2019-09-27
  • Pages : 405
  • ISBN : 1522596895
  • Language : En, Es, Fr & De
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Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.

Advanced Information Systems Engineering

Advanced Information Systems Engineering
31st International Conference, CAiSE 2019, Rome, Italy, June 3–7, 2019, Proceedings

by Paolo Giorgini,Barbara Weber

  • Publisher : Springer
  • Release : 2019-05-28
  • Pages : 702
  • ISBN : 3030212904
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the 31st International Conference on Advanced Information Systems Engineering, CAiSE 2019, held in Rome, Italy, in June 2019. The 41 full papers presented in this volume were carefully reviewed and selected from 206 submissions. The book also contains one invited talk in full paper length. The papers were organized in topical sections named: information system engineering; requirements and modeling; data modeling and analysis; business process modeling and engineering; information system security; and learning and mining in information systems. Abstracts on the CAiSE 2019 tutorials can be found in the back matter of the volume.

Collaborative Efforts for Understanding the Human Brain

Collaborative Efforts for Understanding the Human Brain
A Book

by Sook-Lei Liew,Lianne Schmaal,Neda Jahanshad

  • Publisher : Frontiers Media SA
  • Release : 2019-10-10
  • Pages : 129
  • ISBN : 2889630293
  • Language : En, Es, Fr & De
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The human brain is incredibly complex, and the more we learn about it, the more we realize how much we need a truly interdisciplinary team to make sense of its intricacies. This eBook presents the latest efforts in collaborative team science from around the world, all aimed at understanding the human brain.

Encyclopedia of Bioinformatics and Computational Biology

Encyclopedia of Bioinformatics and Computational Biology
ABC of Bioinformatics

by Anonim

  • Publisher : Elsevier
  • Release : 2018-08-21
  • Pages : 3284
  • ISBN : 0128114320
  • Language : En, Es, Fr & De
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Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases

NoSQL Data Models

NoSQL Data Models
Trends and Challenges

by Olivier Pivert

  • Publisher : John Wiley & Sons
  • Release : 2018-07-30
  • Pages : 278
  • ISBN : 1119544149
  • Language : En, Es, Fr & De
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The topic of NoSQL databases has recently emerged, to face the Big Data challenge, namely the ever increasing volume of data to be handled. It is now recognized that relational databases are not appropriate in this context, implying that new database models and techniques are needed. This book presents recent research works, covering the following basic aspects: semantic data management, graph databases, and big data management in cloud environments. The chapters in this book report on research about the evolution of basic concepts such as data models, query languages, and new challenges regarding implementation issues.

Data and Information Quality

Data and Information Quality
Dimensions, Principles and Techniques

by Carlo Batini,Monica Scannapieco

  • Publisher : Springer
  • Release : 2016-03-23
  • Pages : 500
  • ISBN : 3319241060
  • Language : En, Es, Fr & De
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This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.

Database and Expert Systems Applications

Database and Expert Systems Applications
28th International Conference, DEXA 2017, Lyon, France, August 28-31, 2017, Proceedings, Part I

by Djamal Benslimane,Ernesto Damiani,William I. Grosky,Abdelkader Hameurlain,Amit Sheth,Roland R. Wagner

  • Publisher : Springer
  • Release : 2017-08-11
  • Pages : 517
  • ISBN : 3319644688
  • Language : En, Es, Fr & De
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This two volume set LNCS 10438 and LNCS 10439 constitutes the refereed proceedings of the 28th International Conference on Database and Expert Systems Applications, DEXA 2017, held in Lyon, France, August 2017. The 37 revised full papers presented together with 40 short papers were carefully reviewed and selected from 166 submissions. The papers discuss a range of topics including: Semantic Web and Semantics; Graph Matching; Data Modeling, Data Abstraction, and Uncertainty; Preferences and Query Optimization; Data Integration and RDF Matching; Security and Privacy; Web Search; Data Clustering; Top-K and Skyline Queries; Data Mining and Big Data; Service Computing; Continuous and Temporal Data, and Continuous Query Language; Text Processing and Semantic Search; Indexing and Concurrency Control Methods; Data Warehouse and Data Stream Warehouse; Data Mining and Machine Learning; Recommender Systems and Query Recommendation; Graph Algorithms; Semantic Clustering and Data Classification.

Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019

Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019
Part I

by Leszek Borzemski,Jerzy Świątek,Zofia Wilimowska

  • Publisher : Springer Nature
  • Release : 2019-09-04
  • Pages : 340
  • ISBN : 303030440X
  • Language : En, Es, Fr & De
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This three-volume book highlights significant advances in the development of new information systems technologies and architectures. Further, it helps readers solve specific research and analytical problems and glean useful knowledge and business value from data. Each chapter provides an analysis of a specific technical problem, followed by a numerical analysis, simulation, and implementation of the solution to the real-world problem. Managing an organization, especially in today’s rapidly changing environment, is a highly complex process. Increased competition in the marketplace, especially as a result of the massive and successful entry of foreign businesses into domestic markets, changes in consumer behaviour, and broader access to new technologies and information, calls for organisational restructuring and the introduction and modification of management methods using the latest scientific advances. This situation has prompted various decision-making bodies to introduce computer modelling of organization management systems. This book presents the peer-reviewed proceedings of the 40th Anniversary International Conference “Information Systems Architecture and Technology” (ISAT), held on September 15–17, 2019, in Wrocław, Poland. The conference was organised by the Computer Science Department, Faculty of Computer Science and Management, Wroclaw University of Sciences and Technology, and University of Applied Sciences in Nysa, Poland. The papers have been grouped into three major sections: Part I—discusses topics including, but not limited to, artificial intelligence methods, knowledge discovery and data mining, big data, knowledge-based management, Internet of Things, cloud computing and high-performance computing, distributed computer systems, content delivery networks, and service-oriented computing. Part II—addresses various topics, such as system modelling for control, recognition and decision support, mathematical modelling in computer system design, service-oriented systems, and cloud computing, and complex process modelling. Part III—focuses on a number of themes, like knowledge-based management, modelling of financial and investment decisions, modelling of managerial decisions, production systems management, and maintenance, risk management, small business management, and theories and models of innovation.

Seismic Attributes as the Framework for Data Integration Throughout the Oilfield Life Cycle

Seismic Attributes as the Framework for Data Integration Throughout the Oilfield Life Cycle
A Book

by Kurt J. Marfurt

  • Publisher : SEG Books
  • Release : 2018-01-31
  • Pages : 508
  • ISBN : 1560803517
  • Language : En, Es, Fr & De
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Useful attributes capture and quantify key components of the seismic amplitude and texture for subsequent integration with well log, microseismic, and production data through either interactive visualization or machine learning. Although both approaches can accelerate and facilitate the interpretation process, they can by no means replace the interpreter. Interpreter “grayware” includes the incorporation and validation of depositional, diagenetic, and tectonic deformation models, the integration of rock physics systematics, and the recognition of unanticipated opportunities and hazards. This book is written to accompany and complement the 2018 SEG Distinguished Instructor Short Course that provides a rapid overview of how 3D seismic attributes provide a framework for data integration over the life of the oil and gas field. Key concepts are illustrated by example, showing modern workflows based on interactive interpretation and display as well as those aided by machine learning.

Data Analytics and Management in Data Intensive Domains

Data Analytics and Management in Data Intensive Domains
20th International Conference, DAMDID/RCDL 2018, Moscow, Russia, October 9–12, 2018, Revised Selected Papers

by Yannis Manolopoulos,Sergey Stupnikov

  • Publisher : Springer
  • Release : 2019-07-03
  • Pages : 213
  • ISBN : 303023584X
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the 20th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2018, held in Moscow, Russia, in October 2018. The 9 revised full papers presented together with three invited papers were carefully reviewed and selected from 54 submissions. The papers are organized in the following topical sections: FAIR data infrastructures, interoperability and reuse; knowledge representation; data models; data analysis in astronomy; text search and processing; distributed computing; information extraction from text.

Data Management in Cloud, Grid and P2P Systems

Data Management in Cloud, Grid and P2P Systems
6th International Conference, Globe 2013, Prague, Czech Republic, August 28-29, 2013, Proceedings

by Abdelkader Hameurlain,Wenny Rahayu,David Taniar

  • Publisher : Springer
  • Release : 2013-08-21
  • Pages : 125
  • ISBN : 3642400531
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the 6th International Conference on Data Management in Grid and Peer-to-Peer Systems, Globe 2013, held in Prague, Czech Republic, in August 2013 in conjunction with DEXA 2013. The 10 revised full papers presented were carefully reviewed and selected from 19 submissions. The papers are organized in the following topical sections: data partitioning and consistency; RDF data publishing, querying linked data, and applications; and distributed storage systems and virtualization.

Principles of Big Data

Principles of Big Data
Preparing, Sharing, and Analyzing Complex Information

by Jules J. Berman

  • Publisher : Newnes
  • Release : 2013-05-20
  • Pages : 288
  • ISBN : 0124047246
  • Language : En, Es, Fr & De
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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 Database Management

Principles of Database Management
The Practical Guide to Storing, Managing and Analyzing Big and Small Data

by Wilfried Lemahieu,Seppe vanden Broucke,Bart Baesens

  • Publisher : Cambridge University Press
  • Release : 2018-07-12
  • Pages : 903
  • ISBN : 1107186129
  • Language : En, Es, Fr & De
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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.