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Foundations of Enterprise Data Management

Enterprise Data Management is the global function that facilitates the management of data as a valuable asset of an enterprise.  Its components align to provide the capabilities to manage data as an organization resource. Introduction Enterprise Data Management (EDM) is the global function that facilitates the management of data as a valuable asset of an enterprise.  As defined in the

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Logical and Physical Data Modeling Overview

Logical and physical data modeling are essential components of every organization’s enterprise data architecture, and should form the foundation of every database design.  Standard techniques for logical and physical data modeling enable consistent development and usability.  Even though the concept of data modeling has been around for a long time, in many organizations it is interpreted differently.  According to the

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Increasing the Business Value of Business Intelligence

Organizations can find increased value in business intelligence and analytics efforts through the use of various data delivery strategies. Introduction Like many organizations, your company probably has invested significant time, effort, and money into establishing your data warehousing and business intelligence environment.  You’ve built the databases and the ETL programs to move, clean and integrate data from multiple sources into

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Common People Project Management Challenges

Many project management challenges are centered on the people involved in a project; part of the “people, process, technology” triangle as the basis of all organizations Introduction There are still some common project management challenges, despite the huge efforts from the project management consortiums, project management Subject Matter Experts (SMEs), and many companies that are embracing project management as a

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Challenges to Data Governance Deployment

Challenges to successful data governance deployment are numerous, but can be avoided or overcome through attention to best practices and industry standards Introduction Corporate interest in data governance often starts with recognition within data integration projects that there is a high variability in success and that this can be attributed, partially, to a lack of standardized approaches to data management. Historically

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How Modeling adds Value to a Data Dictionary

A well-modeled data dictionary can provide lasting value and ensure consistency of use throughout an organization for all data elements. Introduction The primary purpose organizations create and maintain a data dictionary is to standardize data content , context, and definitions to achieve consistency, reusability, and quality of the data that drives or supports the organization’s tactical and strategic business initiatives.

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