Explore the essential distinctions between canonical data models and information assets, while uncovering practical insights into their application in business processes and system interfaces.
A new blog post of What’s Your Baseline was published on Sep 15, 2021:
Overview:
This article further explores the nuances of data modeling, distinguishing between canonical data models and information assets. It emphasizes the importance of logical data in application models and interfaces, setting the stage for discussions on physical data modeling.
Core content:
- The article elaborates on the structure of data views, including conceptual/logical decomposition and physical data models.
- It introduces challenges in data modeling, particularly the differentiation between entities and clusters from a business perspective.
- Logical data models are highlighted for their role in simplifying application collaboration diagrams and enhancing clarity in data interfaces.
- The use of cluster models aids in specifying data mapping, which is crucial for maintaining data integrity amidst potential changes in implementation.
Learnings:
- Readers will learn how to define data views and the significance of layering cluster models in canonical data modeling.
- Understanding the role of logical data in application collaboration will be emphasized, encouraging efficient project execution.
- Key strategies for maintaining data integrity through sound logical mapping practices will be discussed.
- Insights into preparing for physical data models and their documentation will enhance readiness for practical implementation.
The original content was published in English.
