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23 Aug, 2019
The Importance of Data Mapping for Data Integration Projects
23 August, 2019
Wayne Yaddrow
Data Integration
Data mapping (source-to-target mapping) is an essential activity for all data integration, business intelligence, and analytics initiatives Introduction Data mapping is among the most important design steps in data migration, data integration, and business intelligence projects. Mapping source to target data greatly influences project success – perhaps more than any other task. The outcome of th
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14 Aug, 2019
Metadata based ETL Transforms Data Integration
14 August, 2019
Fred Zimmerman
Data Integration
Metadata-based extraction, transformation, and loading (ETL) can support a new approach to any organization’s data integration and development practices Introduction Traditional extraction, transformation and loading (ETL) software is a computer programming tool that enables a developer to create custom ETL code. Custom coding is a management challenge with expensive overhead and complex coordin
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23 Mar, 2018
Enterprise Architecture Defined
23 March, 2018
Samuel B. Holcman
More Data Geekery
Samuel B. Holcman An enterprise architecture (EA) is a series of conceptual blueprints that defines the structure and operation of an organization to enable strategic progress. Enterprise Architecture (EA) explicitly describes an organization through a set of independent, non-redundant artifacts, defines how these artifacts relate with each other, and develops a set of prioritized, aligned initiat
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20 Oct, 2015
Foundations of Data Integration
20 October, 2015
Anne Marie Smith, Ph.D.
Data Integration
Data Integration is an essential activity that allows an organization to combine data from disparate sources into a unified version for a variety of uses. Proper data integration starts at architecture, includes understanding requirements and the data, and ends with trusted valid results. Introduction Data integration is the collection of technical and business processes used to combine data fro
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1 Apr, 2016
Data Rationalization and Semantic Resolution
01 April, 2016
Pete Stiglich
More Data Geekery
Data rationalization through managed metadata and data modeling, can support semantic resolution, enabling improved analysis and knowledge transfer. Introduction Across the Internet and within internal systems, ontologies are used to improve search capabilities and make inferences for improved human or computer reasoning. By relating terms in ontology, the user doesn’t need to know the exact ter
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10 Oct, 2005
Facilitate Customer Integration using Generic Dimensional Modeling Techniques
10 October, 2005
Pete Stiglich
Data Integration
Customer data integration can be improved by using generic dimensional modeling techniques Introduction If you are undertaking a Customer Data Integration (CDI) or Customer Master Data Management (MDM) project as part of a dimensional modeling endeavor, how will you tackle the problem of how to store customer addresses? Using customer addresses for direct marketing, analysis of household penetrati
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1 Jul, 2017
The Importance of Data Integration
01 July, 2017
David P. Marco
Data Integration
Following some proven guidelines for data integration will ensure success in data warehousing and business intelligence, analytics and related systems initiatives. Introduction Almost every Chief Information Officer (CIO) has the goal of integrating their organization’s data. In fact, the issue of data integration has risen all the way to the Chief Financial Officer (CFO) and Chief Executive O
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1 Jul, 2016
The Data Constraint to Successful Enterprise Integration
01 July, 2016
Andres Perez
Data Integration
Data Integration is essential for successful information management and business intelligence Introduction Without data integration, enterprise integration is extremely costly and overly complex. Many businesses are convinced that Business Intelligence the Internet, and Customer Relationship Management (CRM) are critical, strategic areas of investment. However, most organizations are strugglin
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