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Security Threats in the Data Warehouse Environment

Data warehouse implementations are vulnerable to internal as well as external security threats.  Follow these mitigating steps to reduce the risks. Introduction Security threats exist against your information resources, whether the systems are accessible through the Internet or buried deep within your internal network, available only to authorized users, including the enterprise data warehouse  and related analytics systems.  The increasing

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Migrating From “Independent” Data Marts

Independent data marts cause many problems in data warehouse architecture; combining to result in numerous issues for business intelligence and analytics solutions. Introduction A severe disease has spread to epidemic proportions throughout our society.  This disease is particularly dangerous as it effects are not readily identifiable at the time of infection.  However if this condition goes untreated it can be

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Metadata Definitions – Common Data Stewardship Activities

Creating and maintaining business and technical metadata definitions are two common data stewardship activities.  Doing them well is essential to data stewardship success. Introduction Data stewards  perform many common activities, including developing and maintaining data domain values, creating and managing business data rules, and supporting the data quality rules, validation and resolution processes.  However, the most common activities performed by

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Observations on Data Strategy

A data strategy can contribute to an organization’s information strategic plan, and arrange for the productive use of the data asset. Introduction A Chief Financial Officer (CFO) was approached by the CEO and asked for an accounting of the company’s financial assets.  The CFO gave a vague response indicating a lack of knowledge of the corporate bank accounts, had little

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Enabling High Quality Analytics through a Data Validity Dimension

Using a specialized data validity dimension in a data warehouse design can support data quality and analytics capabilities. Introduction While working on an Enterprise Data Warehouse for a state court system the issue of poor data quality in the source systems became apparent.  Referential integrity was not strictly enforced and there was very little in the way of attribute level constraints.  One

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Facilitate Customer Integration using Generic Dimensional Modeling Techniques

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 penetration, customer retention

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The Importance of 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 Officer (CEO) level

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