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Principles of Data Integration

Principles of Data Integration
Author: AnHai Doan
Publisher: Elsevier
Total Pages: 522
Release: 2012-06-25
Genre: Computers
ISBN: 0123914795
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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 Resource Integration

Data Resource Integration
Author: Michael H. Brackett
Publisher:
Total Pages: 0
Release: 2012
Genre: Business & Economics
ISBN: 9781935504238
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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.

Customer Data Integration

Customer Data Integration
Author: Jill Dyché
Publisher: John Wiley & Sons
Total Pages: 358
Release: 2011-01-31
Genre: Business & Economics
ISBN: 1118046471
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"Customers are the heart of any business. But we can't succeed if we develop only one talk addressed to the 'average customer.' Instead we must know each customer and build our individual engagements with that knowledge. If Customer Relationship Management (CRM) is going to work, it calls for skills in Customer Data Integration (CDI). This is the best book that I have seen on the subject. Jill Dyché is to be complimented for her thoroughness in interviewing executives and presenting CDI." -Philip Kotler, S. C. Johnson Distinguished Professor of International Marketing Kellogg School of Management, Northwestern University "In this world of killer competition, hanging on to existing customers is critical to survival. Jill Dyché's new book makes that job a lot easier than it has been." -Jack Trout, author, Differentiate or Die "Jill and Evan have not only written the definitive work on Customer Data Integration, they've made the business case for it. This book offers sound advice to business people in search of innovative ways to bring data together about customers-their most important asset-while at the same time giving IT some practical tips for implementing CDI and MDM the right way." -Wayne Eckerson, The Data Warehousing Institute author of Performance Dashboards: Measuring, Monitoring, and Managing Your Business Whatever business you're in, you're ultimately in the customer business. No matter what your product, customers pay the bills. But the strategic importance of customer relationships hasn't brought companies much closer to a single, authoritative view of their customers. Written from both business and technicalperspectives, Customer Data Integration shows companies how to deliver an accurate, holistic, and long-term understanding of their customers through CDI.

Principles of Data Integration

Principles of Data Integration
Author: AnHai Doan
Publisher: Elsevier
Total Pages: 522
Release: 2012-06-25
Genre: Computers
ISBN: 0124160441
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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.

Big Data Integration

Big Data Integration
Author: Xin Luna Dong
Publisher: Morgan & Claypool Publishers
Total Pages: 200
Release: 2015-02-01
Genre: Computers
ISBN: 1627052240
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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.

SQL Server 2012 Data Integration Recipes

SQL Server 2012 Data Integration Recipes
Author: Adam Aspin
Publisher: Apress
Total Pages: 1042
Release: 2013-01-26
Genre: Computers
ISBN: 1430247924
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SQL Server 2012 Data Integration Recipes provides focused and practical solutions to real world problems of data integration. Need to import data into SQL Server from an outside source? Need to export data and send it to another system? SQL Server 2012 Data Integration Recipes has your back. You'll find solutions for importing from Microsoft Office data stores such as Excel and Access, from text files such as CSV files, from XML, from other database brands such as Oracle and MySQL, and even from other SQL Server databases. You'll learn techniques for managing metadata, transforming data to meet the needs of the target system, handling exceptions and errors, and much more. What DBA or developer isn't faced with the need to move data back and forth? Author Adam Aspin brings 10 years of extensive ETL experience involving SQL Server, and especially satellite products such as Data Transformation Services and SQL Server Integration Services. Extensive coverage is given to Integration Services, Microsoft's flagship tool for data integration in SQL Server environments. Coverage is also given to the broader range of tools such as OPENDATASOURCE, linked servers, OPENROWSET, Migration Assistant for Access, BCP Import, and BULK INSERT just to name a few. If you're looking for a resource to cover data integration and ETL across the gamut of Microsoft's SQL Server toolset, SQL Server 2012 Data Integration Recipes is the one book that will meet your needs. Provides practical and proven solutions towards creating resilient ETL environments Clearly answers the tough questions which professionals ask Goes beyond the tools to a thorough discussion of the underlying techniques Covers the gamut of data integration, beyond just SSIS Includes example databases and files to allow readers to test the recipes

Connecting the Data

Connecting the Data
Author: Angelo R Bobak
Publisher: Technics Publications
Total Pages: 0
Release: 2012
Genre: Data integration (Computer science)
ISBN: 9781935504221
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. 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.

Analysis of Integrated Data

Analysis of Integrated Data
Author: Li-Chun Zhang
Publisher: CRC Press
Total Pages: 256
Release: 2019-04-18
Genre: Mathematics
ISBN: 1498727999
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The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.

Enterprise Integration Patterns

Enterprise Integration Patterns
Author: Gregor Hohpe
Publisher:
Total Pages: 737
Release: 2003
Genre:
ISBN: 9788131741177
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Managing Data in Motion

Managing Data in Motion
Author: April Reeve
Publisher: Newnes
Total Pages: 203
Release: 2013-02-26
Genre: Computers
ISBN: 0123977916
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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"