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Principles Of Data Integration

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Principles of Data Integration

Principles of Data Integration Book
Author : AnHai Doan,Alon Halevy,Zachary Ives
Publisher : Elsevier
Release : 2012-06-25
ISBN : 0124160441
Language : En, Es, Fr & De

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Book Description :

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.

Principles of Database Management

Principles of Database Management Book
Author : Wilfried Lemahieu,Seppe vanden Broucke,Bart Baesens
Publisher : Cambridge University Press
Release : 2018-07-12
ISBN : 1107186129
Language : En, Es, Fr & De

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Book Description :

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

Data Lakes

Data Lakes Book
Author : Anne Laurent,Dominique Laurent,Cédrine Madera
Publisher : John Wiley & Sons
Release : 2020-04-09
ISBN : 1119720427
Language : En, Es, Fr & De

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Book Description :

The concept of a data lake is less than 10 years old, but they are already hugely implemented within large companies. Their goal is to efficiently deal with ever-growing volumes of heterogeneous data, while also facing various sophisticated user needs. However, defining and building a data lake is still a challenge, as no consensus has been reached so far. Data Lakes presents recent outcomes and trends in the field of data repositories. The main topics discussed are the data-driven architecture of a data lake; the management of metadata – supplying key information about the stored data, master data and reference data; the roles of linked data and fog computing in a data lake ecosystem; and how gravity principles apply in the context of data lakes. A variety of case studies are also presented, thus providing the reader with practical examples of data lake management.

Principles of Distributed Database Systems

Principles of Distributed Database Systems Book
Author : M. Tamer Özsu,Patrick Valduriez
Publisher : Springer Science & Business Media
Release : 2011-02-24
ISBN : 1441988343
Language : En, Es, Fr & De

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Book Description :

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.

Managing Data in Motion

Managing Data in Motion Book
Author : April Reeve
Publisher : Newnes
Release : 2013-02-26
ISBN : 0123977916
Language : En, Es, Fr & De

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Book Description :

Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types Explains, in non-technical terms, the architecture and components required to perform data integration Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"

Principles of Big Data

Principles of Big Data Book
Author : Jules J. Berman
Publisher : Newnes
Release : 2013-05-20
ISBN : 0124047246
Language : En, Es, Fr & De

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Book Description :

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

Data and Information Quality

Data and Information Quality Book
Author : Carlo Batini,Monica Scannapieco
Publisher : Springer
Release : 2016-03-23
ISBN : 3319241060
Language : En, Es, Fr & De

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Book Description :

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.

Principles of CASE Tool Integration

Principles of CASE Tool Integration Book
Author : Alan W. Brown
Publisher : Oxford University Press on Demand
Release : 1994
ISBN : 0195094786
Language : En, Es, Fr & De

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Book Description :

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.

Real time Linked Dataspaces

Real time Linked Dataspaces Book
Author : Edward Curry
Publisher : Springer Nature
Release : 2019-11-18
ISBN : 3030296652
Language : En, Es, Fr & De

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Book Description :

This open access book explores the dataspace paradigm as a best-effort approach to data management within data ecosystems. It establishes the theoretical foundations and principles of real-time linked dataspaces as a data platform for intelligent systems. The book introduces a set of specialized best-effort techniques and models to enable loose administrative proximity and semantic integration for managing and processing events and streams. The book is divided into five major parts: Part I “Fundamentals and Concepts” details the motivation behind and core concepts of real-time linked dataspaces, and establishes the need to evolve data management techniques in order to meet the challenges of enabling data ecosystems for intelligent systems within smart environments. Further, it explains the fundamental concepts of dataspaces and the need for specialization in the processing of dynamic real-time data. Part II “Data Support Services” explores the design and evaluation of critical services, including catalog, entity management, query and search, data service discovery, and human-in-the-loop. In turn, Part III “Stream and Event Processing Services” addresses the design and evaluation of the specialized techniques created for real-time support services including complex event processing, event service composition, stream dissemination, stream matching, and approximate semantic matching. Part IV “Intelligent Systems and Applications” explores the use of real-time linked dataspaces within real-world smart environments. In closing, Part V “Future Directions” outlines future research challenges for dataspaces, data ecosystems, and intelligent systems. Readers will gain a detailed understanding of how the dataspace paradigm is now being used to enable data ecosystems for intelligent systems within smart environments. The book covers the fundamental theory, the creation of new techniques needed for support services, and lessons learned from real-world intelligent systems and applications focused on sustainability. Accordingly, it will benefit not only researchers and graduate students in the fields of data management, big data, and IoT, but also professionals who need to create advanced data management platforms for intelligent systems, smart environments, and data ecosystems.

Data Stewardship for Open Science

Data Stewardship for Open Science Book
Author : Barend Mons
Publisher : CRC Press
Release : 2018-03-09
ISBN : 1315351145
Language : En, Es, Fr & De

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Book Description :

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional activities broadly aware of the need, complexity, and challenges associated with open science, modern science communication, and data stewardship. The FAIR principles are used as a guide throughout the text, and this book should leave experimentalists consciously incompetent about data stewardship and motivated to respect data stewards as representatives of a new profession, while possibly motivating others to consider a career in the field. The ebook, avalable for no additional cost when you buy the paperback, will be updated every 6 months on average (providing that significant updates are needed or avaialble). Readers will have the opportunity to contribute material towards these updates, and to develop their own data management plans, via the free Data Stewardship Wizard.

Data Integration in the Life Sciences

Data Integration in the Life Sciences Book
Author : 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
ISBN : 3540213007
Language : En, Es, Fr & De

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Book Description :

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.

Connected by Design

Connected by Design Book
Author : Chris Stutzman,Barry Wacksman
Publisher : John Wiley & Sons
Release : 2014-04-28
ISBN : 1118907213
Language : En, Es, Fr & De

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Book Description :

In a world of fierce global competition and rapid technological change, traditional strategies for gaining market share and achieving efficiencies no longer yield the returns they once did. How can companies drive consumer preference and secure sustainable growth in this digital, social, and mobile age? The answer is through functional integration. Some of the world's most highly valued companies—including Amazon, Apple and Google—have harnessed this new business model to build highly interactive ecosystems of interrelated products and digital services, gaining new levels of customer engagement. Functional integration offers forward-looking brands a unique competitive edge by using transformative digital technologies to deliver high-value customer experiences, generate repeat business, and unlock lucrative new business-to-business revenue streams. Connected By Design is the first book to show business leaders and marketers exactly how to use functional integration to achieve transformative growth within any type of company. Based on R/GA's pioneering work with firms at the forefront of functional integration, Barry Wacksman and Chris Stutzman identify seven principles companies must follow in order to create and deliver new value for customers and capture new revenues. Connected By Design explains how functional integration drove the transformation of market-leading companies as diverse as Nike, General Motors, McCormick & Co., and Activision to establish authentic brand relationships with their customers, enter new categories, and develop new sources of income. With Connected by Design, any company can leverage technological disruption to redefine its mission and foster greater brand loyalty and engagement.

Principles of Data Wrangling

Principles of Data Wrangling Book
Author : Tye Rattenbury,Joseph M. Hellerstein,Jeffrey Heer,Sean Kandel,Connor Carreras
Publisher : "O'Reilly Media, Inc."
Release : 2017-06-29
ISBN : 1491938870
Language : En, Es, Fr & De

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Book Description :

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

Developing High Quality Data Models

Developing High Quality Data Models Book
Author : Matthew West
Publisher : Elsevier
Release : 2011-02-07
ISBN : 9780123751072
Language : En, Es, Fr & De

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Book Description :

Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models. The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool. This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling. Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates Develops ideas for creating consistent approaches to high quality data models

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 Book
Author : Kurt J. Marfurt
Publisher : SEG Books
Release : 2018-01-31
ISBN : 1560803517
Language : En, Es, Fr & De

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Book Description :

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.

Entity Resolution and Information Quality

Entity Resolution and Information Quality Book
Author : John R. Talburt
Publisher : Elsevier
Release : 2011-01-14
ISBN : 9780123819734
Language : En, Es, Fr & De

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Book Description :

Entity Resolution and Information Quality presents topics and definitions, and clarifies confusing terminologies regarding entity resolution and information quality. It takes a very wide view of IQ, including its six-domain framework and the skills formed by the International Association for Information and Data Quality {IAIDQ). The book includes chapters that cover the principles of entity resolution and the principles of Information Quality, in addition to their concepts and terminology. It also discusses the Fellegi-Sunter theory of record linkage, the Stanford Entity Resolution Framework, and the Algebraic Model for Entity Resolution, which are the major theoretical models that support Entity Resolution. In relation to this, the book briefly discusses entity-based data integration (EBDI) and its model, which serve as an extension of the Algebraic Model for Entity Resolution. There is also an explanation of how the three commercial ER systems operate and a description of the non-commercial open-source system known as OYSTER. The book concludes by discussing trends in entity resolution research and practice. Students taking IT courses and IT professionals will find this book invaluable. First authoritative reference explaining entity resolution and how to use it effectively Provides practical system design advice to help you get a competitive advantage Includes a companion site with synthetic customer data for applicatory exercises, and access to a Java-based Entity Resolution program.

Data Visualization

Data Visualization Book
Author : Alexandru C. Telea
Publisher : CRC Press
Release : 2014-09-18
ISBN : 1466585269
Language : En, Es, Fr & De

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Book Description :

Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration with third-party code, and more. Focusing on those techniques and methods with the broadest applicability across fields, the second edition of Data Visualization: Principles and Practice provides a streamlined introduction to various visualization techniques. The book illustrates a wide variety of applications of data visualizations, illustrating the range of problems that can be tackled by such methods, and emphasizes the strong connections between visualization and related disciplines such as imaging and computer graphics. It covers a wide range of sub-topics in data visualization: data representation; visualization of scalar, vector, tensor, and volumetric data; image processing and domain modeling techniques; and information visualization. See What’s New in the Second Edition: Additional visualization algorithms and techniques New examples of combined techniques for diffusion tensor imaging (DTI) visualization, illustrative fiber track rendering, and fiber bundling techniques Additional techniques for point-cloud reconstruction Additional advanced image segmentation algorithms Several important software systems and libraries Algorithmic and software design issues are illustrated throughout by (pseudo)code fragments written in the C++ programming language. Exercises covering the topics discussed in the book, as well as datasets and source code, are also provided as additional online resources.

The Principles of Integrated Technology in Avionics Systems

The Principles of Integrated Technology in Avionics Systems Book
Author : Guoqing Wang,Wenhao Zhao
Publisher : Academic Press
Release : 2020-01-17
ISBN : 012816560X
Language : En, Es, Fr & De

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Book Description :

The Principles of Integrated Technology in Avionics Systems describes how integration can improve flight operations, enhance system processing efficiency and equip resource integration. The title provides systematic coverage of avionics system architecture and ground system integration. Looking beyond hardware resource sharing alone, it guides the reader through the benefits and scope of a modern integrated avionics system. Integrated technology enhances the performance of organizations by improving system capacity and boosting efficiency. Avionics systems are the functional center of aircraft systems. System integration technology plays a vital role in the complex world of avionics and an integrated avionics system will fully-address systems, information and processes. Introduces integration technology in complex avionics systems Guides the reader through the scope and benefits of avionic system integration Gives practical guidance on using integration to optimize an avionics system Describes the basis of avionics system architecture and ground system integration Presents modern avionics as a system that is becoming increasingly integrated

Big Data For Dummies

Big Data For Dummies Book
Author : Judith S. Hurwitz,Alan Nugent,Fern Halper,Marcia Kaufman
Publisher : John Wiley & Sons
Release : 2013-04-02
ISBN : 1118644174
Language : En, Es, Fr & De

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Book Description :

Find the right big data solution for your business ororganization Big data management is one of the major challenges facingbusiness, industry, and not-for-profit organizations. Data setssuch as customer transactions for a mega-retailer, weather patternsmonitored by meteorologists, or social network activity can quicklyoutpace the capacity of traditional data management tools. If youneed to develop or manage big data solutions, you'll appreciate howthese four experts define, explain, and guide you through this newand often confusing concept. You'll learn what it is, why itmatters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importanceto businesses, not-for-profit organizations, government, and ITprofessionals Authors are experts in information management, big data, and avariety of solutions Explains big data in detail and discusses how to select andimplement a solution, security concerns to consider, data storageand presentation issues, analytics, and much more Provides essential information in a no-nonsense,easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helpsyou take charge of big data solutions for your organization.

Big Data Integration

Big Data Integration Book
Author : Xin Luna Dong,Divesh Srivastava
Publisher : Springer Nature
Release : 2022-05-31
ISBN : 3031018532
Language : En, Es, Fr & De

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Book Description :

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.