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Data Quality

Data quality is essential to interoperability and is founded on database design standards, and data standardization. That is, defining and managing enterprise-wide data semantics. Whitemarsh offers a number of materials focused on data quality and data standardization. The metadata repository stores data semantics in the metabase.

Whitemarsh's data quality programs are self-rewarding. That is, the more Whitemarsh's data quality programs are employed, the faster work is accomplished. Staff utilizing the Whitemarsh methodology become more productive, resulting in deliverables being created at a lower cost with higher quality.

 

A Column By Any Other Name is Not a Data Element PresentationForm: PaperSample?
Updated Quarter 4, 2005
Updated for ISO-11179
 
A Column By Any Other Name is Not a Data Element PresentationForm: CourseSample?
Updated Quarter 4, 2005
Updated for ISO-11179
 
A Column By Any Other Name is Not a Data Element Presentation - Short CourseForm: CourseSample?
Updated Quarter 4, 2005
A Column By Any Other Name is Not a Data Element Presentation - Short Course
 
Achieving Data StandardizationForm: BookSample?
Updated Quarter 4, 2005
This book presents an analysis of the problems that undercut data standardization with respect to standard values and standard metadata. The book then provides an approach, meta models, and a work breakdown structure that can be used to implement data standardization projects within the enterprise.
 
Achieving Data Standardization Long TalkForm: CourseSample?
Updated Quarter 4, 2005
This short course presents an analysis of the problems that undercut data standardization with respect to standard values and standard metadata. This one day course presents an approach, meta models, and a work breakdown structure that can be used to implement data standardization projects within the enterprise.
 
Achieving Data Standardization Short TalkForm: CourseSample?
Updated Quarter 4, 2005
This long course presents an analysis of the problems that undercut data standardization with respect to standard values and standard metadata. This one day course presents an approach, meta models, and a work breakdown structure that can be used to implement data standardization projects within the enterprise.
 
Achieving Enterprise Wide Data Semantics StandardizationForm: CourseSample?
Updated Quarter 4, 2005
This course identifies the key problems that prevent an enterprise from achieving data standardization. The course the presents a strategy for overcoming these problem areas.
 
An Old Saw That Just Wont CutForm: PaperSample?
Updated Quarter 4, 2005
The "old saw" at issue in this paper is the traditional three part paradigm approach for data element names: prime word, modifier[s], and class word. This old saw just won't cut. Never did, and never will. The paper exhorts readers to stop wasting their time and money and choose one that does. This paper then identifies and describes the five main problems with the traditional approach and then presents an approach that since its introduction in 1981, has lowered cost and risk, and increased speed and quality.
 
An Old Saw That Just Wont Cut - Software Implementation ReportForm: PaperSample?
Updated Quarter 4, 2005
This paper, An Olde Saw That Just Won't Cut, A Software Implementation Follow-up is based on its predecessor article, An Olde Saw That Just Don't Cut which showed how the "old saw" about data elements (prime word, modifier[s], and a single class word) "just don't cut" because of five mistaken notions (i.e., the olde saw's teeth). This paper reports on that accomplishment, both in terms the of accomplishment and in terms of the five teeth.
 
Analysis of the DISA 8320 Data Standardization ApproachForm: PaperSample?
This paper presents an analysis of the Data Standardization Procedures employed by the United States Department of Defense's Information Systems Agency (DISA). Their approach is fatally flawed in a number of different areas and is an example of an approach that should be avoided.
 
Data Standardization Work PlanForm: PaperSample?
Updated Quarter 4, 2005
This paper presents a detailed set of steps to acheive data standardization within an enterprise.
 
The Data Standardization ProblemForm: CourseSample?
Updated Quarter 4, 2005
 

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