Principles Of Data Integration
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Principles Of Data Integration
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Author : AnHai Doan
language : en
Publisher: Elsevier
Release Date : 2012-06-25
Principles Of Data Integration written by AnHai Doan and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-25 with Computers categories.
Principles of Data Integration is the first comprehensive textbook of data integration, covering theoretical principles and implementation issues as well as current challenges raised by the semantic web and cloud computing. The book offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand. Readers will also learn how to build their own algorithms and implement their own data integration application. 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. This text is an ideal resource for database practitioners in industry, including data warehouse engineers, database system designers, data architects/enterprise architects, database researchers, statisticians, and data analysts; students in data analytics and knowledge discovery; and other data professionals working at the R&D and implementation levels. 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
Data Integration Blueprint And Modeling
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Author : Anthony David Giordano
language : en
Publisher: Pearson Education
Release Date : 2010-12-27
Data Integration Blueprint And Modeling written by Anthony David Giordano and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-27 with Business & Economics categories.
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
Principles Of Data Integration
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Author : AnHai Doan
language : en
Publisher: Elsevier
Release Date : 2012-06-25
Principles Of Data Integration written by AnHai Doan and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-25 with Computers categories.
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.
Principles Of Data Fabric
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Author : Sonia Mezzetta
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-04-06
Principles Of Data Fabric written by Sonia Mezzetta and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-06 with Computers categories.
Apply Data Fabric solutions to automate Data Integration, Data Sharing, and Data Protection across disparate data sources using different data management styles. Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn to design Data Fabric architecture effectively with your choice of tool Build and use a Data Fabric solution using DataOps and Data Mesh frameworks Find out how to build Data Integration, Data Governance, and Self-Service analytics architecture Book Description Data can be found everywhere, from cloud environments and relational and non-relational databases to data lakes, data warehouses, and data lakehouses. Data management practices can be standardized across the cloud, on-premises, and edge devices with Data Fabric, a powerful architecture that creates a unified view of data. This book will enable you to design a Data Fabric solution by addressing all the key aspects that need to be considered. The book begins by introducing you to Data Fabric architecture, why you need them, and how they relate to other strategic data management frameworks. You'll then quickly progress to grasping the principles of DataOps, an operational model for Data Fabric architecture. The next set of chapters will show you how to combine Data Fabric with DataOps and Data Mesh and how they work together by making the most out of it. After that, you'll discover how to design Data Integration, Data Governance, and Self-Service analytics architecture. The book ends with technical architecture to implement distributed data management and regulatory compliance, followed by industry best practices and principles. By the end of this data book, you will have a clear understanding of what Data Fabric is and what the architecture looks like, along with the level of effort that goes into designing a Data Fabric solution. What you will learn Understand the core components of Data Fabric solutions Combine Data Fabric with Data Mesh and DataOps frameworks Implement distributed data management and regulatory compliance using Data Fabric Manage and enforce Data Governance with active metadata using Data Fabric Explore industry best practices for effectively implementing a Data Fabric solution Who this book is for If you are a data engineer, data architect, or business analyst who wants to learn all about implementing Data Fabric architecture, then this is the book for you. This book will also benefit senior data professionals such as chief data officers looking to integrate Data Fabric architecture into the broader ecosystem.
Principles Of Database Management
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Author : Wilfried Lemahieu
language : en
Publisher: Cambridge University Press
Release Date : 2018-07-12
Principles Of Database Management written by Wilfried Lemahieu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-12 with Computers categories.
Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.
Principles Of Data Wrangling
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Author : Tye Rattenbury
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-06-29
Principles Of Data Wrangling written by Tye Rattenbury and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-29 with Computers categories.
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 Big Data
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Author : Jules J. Berman
language : en
Publisher: Newnes
Release Date : 2013-05-20
Principles Of Big Data written by Jules J. Berman and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-20 with Computers categories.
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
The Definitive Guide To Data Integration
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Author : Pierre-Yves BONNEFOY
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29
The Definitive Guide To Data Integration written by Pierre-Yves BONNEFOY and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Computers categories.
Learn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stack Key Features Learn how to leverage modern data stack tools and technologies for effective data integration Design and implement data integration solutions with practical advice and best practices Focus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologies Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.What you will learn Discover the evolving architecture and technologies shaping data integration Process large data volumes efficiently with data warehousing Tackle the complexities of integrating large datasets from diverse sources Harness the power of data warehousing for efficient data storage and processing Design and optimize effective data integration solutions Explore data governance principles and compliance requirements Who this book is for This book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you’re a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape.
Connecting The Data
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Author : Angelo R Bobak
language : en
Publisher: Technics Publications
Release Date : 2012
Connecting The Data written by Angelo R Bobak and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Data integration (Computer science) categories.
. 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.
Data Resource Integration
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Author : Michael H. Brackett
language : en
Publisher:
Release Date : 2012
Data Resource Integration written by Michael H. Brackett and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Business & Economics categories.
Data Resource Integration explains how to go about understanding and resolving a disparate data resource and creating a comparate data resource that fully meets an organization's current and future business information demand.