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The Enterprise Data Model: Enhancing Generative AI with Business Knowledge

Discover the pivotal role of Entity Relationship (ER) Modeling in business knowledge management for Generative AI. Industry experts Don Gooldy and Jamie Knowles demonstrate how ER Modeling, using ER/Studio, outperforms current graph modeling interfaces in authoring business knowledge for Large Language Models (LLMs). This webinar reveals how the ER modeling approach better aligns with business needs and forms a robust knowledge foundation for LLMs. Learn how to integrate enterprise data into Generative AI functionality, paving the way for enhanced AI-driven business solutions.

ER Modeling & Gen AI Topics Covered:

  • Preventing AI Hallucinations
    • Learn strategies to ensure your AI produces accurate and reliable information.
  • Leveraging Metadata
    • Discover how to use your existing metadata to train AI models effectively.
  • Understanding Key Data Concepts
    • Gain insights into the differences and interactions between Knowledge Graphs, Data Catalogs, Business Glossaries, and Data Models.
  • Integrating Knowledge Structures
    • Explore methods for combining various data structures to create a comprehensive knowledge base.
  • Enhancing LLMs with Knowledge Graphs
    • Understand how structured, interconnected facts improve the performance of LLMs.
    • Emphasize the importance of quality knowledge and completeness for accurate AI outcomes.
  • Aligning ER and Knowledge Graph Models
    • Recognize the similarities between ER models, UML, and Knowledge Graphs.
    • In these models, learn about nodes/entities, properties/attributes, and relationships/edges.
  • Historical Perspectives on Data Modeling
    • Explore contributions from E. F. Codd, Peter Chen, and Clive Finkelstein to modern data modeling.
    • Understand the role of narrative expressions in business functions.
  • Using Ontology and Taxonomy
    • Learn how to classify business functions through shared characteristics and differences.
    • Combine ontology and taxonomy for a robust knowledge methodology.

Plus, watch a live demo using Accenture’s AUDM Insurance Enterprise Business Architecture Model, showcasing the creation of a Relational Data Warehouse Solution and a flow of information and dependencies. Gain valuable insights from Don Gooldy, a seasoned Data Architecture Innovation Senior Principal at Accenture with over three decades of experience in data and business architecture. Learn why he prefers ER/Studio over other ER Modeling tools.

To learn more about Ontology & Taxonomy, check out Don Goodly’s article series covering the intricacies of these two complementary classification methods.

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