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The Evolution of the Corporate Information Factory

Introduction In the beginning were applications.  And applications served the corporation well until there was a desire for integration of historical information. However, applications supported neither integration nor historical data.  When it was noticed that applications – once built and put into production – were unable to be reshaped, the limitations of trying to get information out of applications became

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Building a Data Warehouse in Iterations

Effective data warehouse development requires an iterative approach that results in a robust, well-defined and usable system for analytics. This article is excerpted from Data Warehouse Project Management (Addison-Wesley, Adelman and Moss, © September 2000). Data Warehouse Iterations Introduction A data warehouse cannot and should not be built in one Big Bang. Instead, a data warehouse is an evolving system

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Should We Model Everything?

Different models represent and communicate different types of data; all are important to effective data management. Introduction The level of attention paid to a data model should be determined by its intended use and place in the enterprise. There are different types of models that represent different types of data, all of which should be “touched” by data administration. The

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Practical Data Management Tips

Five Commandments of practical data management can ensure that fundamental best practices are followed consistently Introduction Commandments are like best practices (see the DAMA-DMBOK©); they are basic performance statements.  In data management there are some practical, fundamental administrative rules for behavior.  These are commandments and should only be compromised when there is no other option (I would like to say

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The Data Constraint to Successful Enterprise 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 struggling to deploy the enabling technologies.  What are the constraints that prevent businesses

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Data Warehouse Costs

Developing a process for cost justifying a data warehouse and metrics for measuring various costs associated with a data warehouse project are essential for success This article is excerpted from a book titled Data Warehouse Project Management (published by Addison Wesley Longman (© 2000), Sid Adelman, Larissa Moss) Introduction Not every data warehouse project will be cost justified initially.  Many

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Data Warehouse Success Measures

Knowing how to measure success and failure, and qualifying results for a data warehouse or analytics project is essential for all project managers. This article is excerpted from a book titled Data Warehouse Project Management (published by Addison Wesley Longman (© 2000), Sid Adelman, Larissa Moss) Introduction There has been much heated discussion over the failure rate of data warehouses

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