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TDWI White Paper Library

TDWI is proud to maintain this library as a valuable resource for business intelligence and data warehousing professionals seeking to augment their knowledge of tools, solutions, and industry best practices. The content in this repository is created by our many partners in the BI/DW hardware, software, and consulting markets.

See the most recent white papers below.

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Business Rules White Papers

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Advancing the Data Agenda: Roles and Responsibilities in the Data Quality Trenches

Advancing the Data Agenda: Roles and Responsibilities in the Data Quality Trenches

It is high-minded to observe that any data program (data governance, master data management, data analytics, data modeling, etc.) requires a full partnership between business and IT. The real world is more mundane and far more demanding than that. Indeed, success with any data program depends on getting the right groups involved and assigning the right people the right roles and responsibilities. This white paper addresses the question, "who, specifically, are those right groups and right people?" on two levels. It also highlights underlying principles that, properly applied, lead to solid answers to the "who" questions for a wide variety of scenarios.


The Practitioners Guide to Data Profiling

The Practitioner's Guide to Data Profiling

Data profiling has become the de facto starting point for practically any data-oriented project because it uncovers potential issues and provides valuable insight into your data. Its ability to summarize details about large data sets from different angles makes it a powerful tool for analysts -– yet without specific direction, there is a risk of “analysis paralysis” that prevents business objectives from being realized. To fully achieve the power and benefits of data profiling, it’s important to clarify analysis processes and techniques that use the technology. This white paper addresses data profiling techniques that can help the analyst understand the empirical truth associated with enterprise data.


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