By Pete Stiglich Compares enterprise conceptual data models (covering broad domains and shared definitions) with project-level conceptual models (scoped to a specific initiative). It notes…
Meta Data Management and Migration to ICD-10
By Pete Stiglich Discusses why the transition from ICD‑9 to ICD‑10 is high-stakes and complex for providers and payers: code mappings are often not 1:1,…
Performance Benefits of Surrogate Keys in Dimensional Models
By Pete Stiglich Explains why dimensional warehouses typically use surrogate keys in dimensions instead of relying on natural keys from source systems. Small numeric surrogate…
Realizing Optimal Value from Cloud Migration
By Pete Stiglich Focuses on how cloud migrations deliver the most value when they are coupled with architectural modernization rather than simple ‘lift and shift.’…
Steps to Convert Logical to Physical Data Models
By Pete Stiglich Explains how a logical data model is refined into a physical implementation. Typical steps include selecting DBMS-specific data types, applying naming abbreviations…
The Conceptual Data Model – Key to Integration
By Pete Stiglich Argues that integration succeeds when organizations align on shared business meaning, not just field mappings. A conceptual data model becomes the semantic…
The Semantic Web and Information Architecture
By Pete Stiglich Explains how Semantic Web standards (such as RDF/OWL and related querying) can strengthen information architecture by making meaning explicit and machine-interpretable. Rather…
The Semantic Web and Metadata Management
By Pete Stiglich The EIMInstitute ‘Current Issue’ listing describes this as the third installment in a series on the Semantic Web and Enterprise Information Management…
The Holy Grail of Analytics?
By Pete Stiglich The end goal of analytics is to be able to make data-driven decisions — sooner rather than later. Of course, it is…
Ignoring Your Customer
By W H Inmon In the early days of data warehousing, I was invited to talk to a CEO and a CIO at a well-known…
