Data Modeling Mastery:
Structuring Data for AI, Analytics, or anything else

A model is developed for a purpose. This presentation explores the critical role of data modeling and data architecture as foundational to AI, analytics, or any subsequent use of data.  Clear, documented data models act as the "digital blueprints,” enabling a common understanding among business users, technical personnel, and systems.  Suboptimal data modeling practices accumulate "data debt" and lead to complex, brittle systems.  Data models are a stable, reusable component of any system and are the most reliable means of conveying the enormous amount of information required for effective data management.  Understanding the strengths of each of the three data modeling types will prepare you with a more robust analysis toolkit.  Using reverse engineering analysis, delegates will follow the lifecycle of a set of data as it is prepared for subsequent use.

 

Program learning objectives include:

 

-  How to incorporate AI in your modeling efforts 

-  Understanding the role played by the
    various model types

-  Differentiate appropriately use among
    conceptual, logical, and physical data models

-  Understand the rigor of the round-trip
    data reengineering analyses

-  Apply appropriate use of various data modeling types