Principles of Data Integration Book

Principles of Data Integration


  • Author : AnHai Doan
  • Publisher : Elsevier
  • Release Date : 2012-06-25
  • Genre: Computers
  • Pages : 520
  • ISBN 10 : 9780123914798

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Principles of Data Integration Excerpt :

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 Book

Principles of Data Integration


  • Author : AnHai Doan
  • Publisher : Elsevier
  • Release Date : 2012
  • Genre: Computers
  • Pages : 497
  • ISBN 10 : 9780124160446

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Principles of Data Integration Excerpt :

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.

Data Lakes Book

Data Lakes


  • Author : Anne Laurent
  • Publisher : John Wiley & Sons
  • Release Date : 2020-04-09
  • Genre: Computers
  • Pages : 244
  • ISBN 10 : 9781119720423

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Data Lakes Excerpt :

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 Book
Score: 4
From 4 Ratings

Principles of Distributed Database Systems


  • Author : M. Tamer Özsu
  • Publisher : Springer Science & Business Media
  • Release Date : 2011-02-24
  • Genre: Computers
  • Pages : 846
  • ISBN 10 : 9781441988348

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Principles of Distributed Database Systems Excerpt :

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 Database Management Book

Principles of Database Management


  • Author : Wilfried Lemahieu
  • Publisher : Cambridge University Press
  • Release Date : 2018-07-12
  • Genre: Computers
  • Pages : 903
  • ISBN 10 : 9781107186125

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Principles of Database Management Excerpt :

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

Principles of Big Data Book

Principles of Big Data


  • Author : Jules J. Berman
  • Publisher : Newnes
  • Release Date : 2013-05-20
  • Genre: Computers
  • Pages : 288
  • ISBN 10 : 9780124047242

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Principles of Big Data Excerpt :

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 Book

Data and Information Quality


  • Author : Carlo Batini
  • Publisher : Springer
  • Release Date : 2016-03-23
  • Genre: Computers
  • Pages : 500
  • ISBN 10 : 9783319241067

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Data and Information Quality Excerpt :

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

Principles of Data Wrangling Book

Principles of Data Wrangling


  • Author : Tye Rattenbury
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2017-06-29
  • Genre: Computers
  • Pages : 94
  • ISBN 10 : 9781491938874

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Principles of Data Wrangling Excerpt :

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

Managing Data in Motion Book

Managing Data in Motion


  • Author : April Reeve
  • Publisher : Newnes
  • Release Date : 2013-02-26
  • Genre: Computers
  • Pages : 204
  • ISBN 10 : 9780123977915

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Managing Data in Motion Excerpt :

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"

Data Stewardship for Open Science Book

Data Stewardship for Open Science


  • Author : Barend Mons
  • Publisher : CRC Press
  • Release Date : 2018-03-09
  • Genre: Business & Economics
  • Pages : 226
  • ISBN 10 : 9781315351148

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Data Stewardship for Open Science Excerpt :

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.

Principles of CASE Tool Integration Book

Principles of CASE Tool Integration


  • Author : Alan W. Brown
  • Publisher : Oxford University Press on Demand
  • Release Date : 1994
  • Genre: Religion
  • Pages : 271
  • ISBN 10 : 9780195094787

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Principles of CASE Tool Integration Excerpt :

Expertly written by top experts, 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.

Connected by Design Book

Connected by Design


  • Author : Chris Stutzman
  • Publisher : John Wiley & Sons
  • Release Date : 2014-04-28
  • Genre: Business & Economics
  • Pages : 256
  • ISBN 10 : 9781118907214

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Connected by Design Excerpt :

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.

Data Visualization Book

Data Visualization


  • Author : Alexandru C. Telea
  • Publisher : CRC Press
  • Release Date : 2014-09-18
  • Genre: Computers
  • Pages : 617
  • ISBN 10 : 9781466585263

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Data Visualization Excerpt :

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.

Connecting the Data Book

Connecting the Data


  • Author : Angelo R. Bobak
  • Publisher : Technics Publications
  • Release Date : 2012-10-01
  • Genre: Computers
  • Pages : 248
  • ISBN 10 : 9781634620352

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Connecting the Data Excerpt :

Business data integration is a complex problem that must be solved when organizations change or enhance their internal structures. The goal of this book is to present a simple yet thorough resource that describes the challenges of business data integration and the solutions to these challenges such as schema integration, illustrated through an Operational Data Store (ODS) case study. This book contains three sections spanning ten chapters. Section I, Foundational Concepts, will provide you with the necessary basic concepts and discuss schema integration. Section II, Preparation and Design, introduces the case study and we will reverse engineer each of the data sources to create a set of data dictionary reports which will provide us with the meta data we need to apply the schema integration process. Section III, Physical Implementation, will present scripts to populate each of the source databases and spreadsheets and use reports to create Extract, Transform, and Load (ETL) specifications. The ten chapters within these three sections are: • Chapter 1 – Introduction and Roadmap • Chapter 2 – What is an Operational Data Store (ODS)? • Chapter 3 – What is Schema Integration? • Chapter 4 – The Role of the ODS within DW Architectures • Chapter 5 – Reverse Engineering the four Source Schema • Chapter 6 – Designing the Interim Schema • Chapter 7 – Preparing the ETL Specifications • Chapter 8 – Designing the Physical ODS Database Model • Chapter 9 – Designing Our ETL processes with SSIS • Chapter 10 – Data Quality Profiling

Big Data Integration Book

Big Data Integration


  • Author : Xin Luna Dong
  • Publisher : Morgan & Claypool Publishers
  • Release Date : 2015-02-01
  • Genre: Computers
  • Pages : 198
  • ISBN 10 : 9781627052245

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Big Data Integration Excerpt :

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.