Evaluating Software Complexity Measures
IEEE Transactions on Software Engineering
Property-Based Software Engineering Measurement
IEEE Transactions on Software Engineering
Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
Software metrics (2nd ed.): a rigorous and practical approach
Software metrics (2nd ed.): a rigorous and practical approach
Communications of the ACM
Data warehouse design solutions
Data warehouse design solutions
Improving data warehouse and business information quality: methods for reducing costs and increasing profits
Building Knowledge through Families of Experiments
IEEE Transactions on Software Engineering
Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
Information modeling and method engineering: a psychological perspective
Journal of Database Management - Special issue on information modeling methods
Principles of survey research: part 1: turning lemons into lemonade
ACM SIGSOFT Software Engineering Notes
A Framework of Software Measurement
A Framework of Software Measurement
The Architecture of Cognition
Data Warehousing in Action
Object Oriented Design Measurement
Object Oriented Design Measurement
The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom
Fundamentals of Data Warehouses
Fundamentals of Data Warehouses
Information and Database Quality
Information and Database Quality
Data Warehousing; Building the Corporate Knowledge Base
Data Warehousing; Building the Corporate Knowledge Base
Multidimensional Database Technology
Computer
Towards A Theoretical Framework For Measuring Software Attributes
METRICS '97 Proceedings of the 4th International Symposium on Software Metrics
International Journal of Business Intelligence and Data Mining
Hybrid methodology for data warehouse conceptual design by UML schemas
Information and Software Technology
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This chapter proposes a set of metrics to assess data warehouse quality. A set of data warehouse metrics is presented, and the formal and empirical validations that have been done with them. As we consider that information is the main organizational asset, one of our primary duties should be assuring its quality. Although some interesting guidelines have been proposed for designing "good" data models for data warehouses, more objective indicators are needed. Metrics are a useful objective mechanism for improving the quality of software products and also for determining the best ways to help professionals and researchers. In this way, our goal is to elaborate a set of metrics for measuring data warehouse quality which can help designers in choosing the best option among more than one alternative design.