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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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Data Mart Migration

Fully architected solutions to data warehouse / analytics systems, not independent data marts, is the right way to ensure all the benefits of integrated data Introduction The need for an architected solution to decision support / analytics data, as opposed to the proliferation of independent data marts is becoming increasingly apparent.  The spread of independent data marts  have created “islands

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Stranded on Islands of Data

Independent data marts create stranded, unusable data.  Independent data marts can spread like a disease through an organization and must be eradicated. There is a severe disease that has spread to epidemic proportions throughout our society. This disease is particularly dangerous as its effects are not readily identifiable at the time of infection. However, if this condition goes untreated, it

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