By Pete Stiglich Identifies core data management practices that enable real trust in data: strong data governance with meaningful business participation, robust data architecture and…
Database inferencing to get to trusted healthcare data
By Pete Stiglich Describes building a data-quality rule repository for a healthcare EDW program focused on ‘trusted data.’ The author explains storing configurable quality rules,…
Enabling High Quality Analytics through a Data Validity Dimension
By Pete Stiglich Explains a practical dimensional-modeling pattern for handling imperfect source data without destroying analytical trust. Instead of rejecting records with invalid dates or…
The Power of Dimension Placeholder Records
By Pete Stiglich In a dimensional model, how do you handle missing or invalid values in a fact table source record that are used to…
Examining and Refuting Some Common Data Governance Myths
By Anne Marie Smith, Ph.D., FIDM, ADGP Many organizations are hesitant to develop a data management/data governance program since they believe common myths about the…
Conceptual Modeling to Enhance Data Quality
By Pete Stiglich Explores how conceptual modeling improves data quality by forcing clarity on business concepts, definitions, and the rules that connect them. By identifying…
Data Integrity in a New Light – A New View of Data Management and Ethics
By Anne Marie Smith, Ph.D., FIDM, ADGP A new definition of data integrity focuses on an ethical approach to managing and using data, providing an…
