One-Day Distance Learning Masterclass

AI Data Modeling Masterclass

Build stronger AI initiatives by learning how to create practical, human-consumable data representations that connect business understanding with technical implementation.

Join Business Architecture Center Of Excellence™ for a practitioner-led, one-day Masterclass focused on Data Architecture Modeling, AI-driven Data Modeling, Data DNA, and the methods needed to improve how data supports artificial intelligence and machine learning initiatives.

October 13, 2026 · 9:00 AM to 5:00 PM Eastern Time · $899 USD

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Practical Data Modeling for AI

Build the Data Understanding Behind Better AI

AI performance depends heavily on how well data is understood, structured, represented, and communicated. This Masterclass gives participants practical methods and techniques for developing Data Models that support both business stakeholders and technology teams.

AI-Driven Data Modeling

Learn the fundamentals of structuring and representing data to support more effective AI and machine learning initiatives.

Your Organization's Data DNA

Learn about the three models, including stakeholder models and technology-enabling models, used to represent and communicate your organization's Data DNA.

Business and Technical Alignment

Bridge the gap between how business stakeholders understand data and how technical teams translate those requirements into implementation.

Human-Consumable Data Representations

Develop representations that make complex data easier for stakeholders, architects, analysts, and technical teams to understand and use.

AI Hallucinations and Fabrications

Understand how weaknesses in data understanding and representation can contribute to unreliable AI results, including hallucinations and fabricated outputs.

Public Large Language Model Risks

Examine risks associated with the use of public large language models and why organizations need stronger understanding of the data involved in AI initiatives.

Practice, Not Quizzes

Apply the methods and techniques through practical exercises under the guidance of an experienced practitioner rather than relying on exam-style testing.

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Who Should Attend

Designed for Business and Technology Professionals Working With Data and AI

No prerequisites are required to enroll in the AI Data Modeling Masterclass.

The session is appropriate for professionals who need to understand, communicate, structure, or apply data within AI, machine learning, Business Architecture, Enterprise Architecture, and other data-intensive initiatives.

Participants may include:

Data Scientists
AI Engineers
Business Architects
Enterprise Architects
Business Stakeholders
Business Analysts
Information Professionals
IT Professionals
Professionals involved in AI and machine learning projects
Anyone interested in producing human-consumable data representations

Man pointing to data charts on a vertical display while two colleagues review the figures

Cover of the BACOE Business Architecture Certification Workshop brochure

What Is Included

Continue Applying What You Learn After the Masterclass

The Masterclass is designed to provide resources and support that extend beyond the one-day session.

Presentation Materials

Attendees receive copies of the Masterclass presentation materials so they can revisit the concepts, methods, and techniques after the session.

Practitioner Support

BACOE practitioners offer one-on-one follow-up sessions or remote coaching calls to help attendees apply what they learned and address specific challenges.

Two Included Publications

Masterclass attendees also receive two publications:

Business Architecture: The Enabler of Business Strategy
Reaching the Pinnacle: Implementing and Managing Enterprise Architecture

These resources provide additional material for continued professional development and application.

From Modeling to Application

What You Can Apply After the Masterclass

The value of Data Modeling is not limited to producing diagrams. The techniques covered in the Masterclass can be applied across AI, machine learning, data quality, integration, Business Intelligence, and organizational decision-making.

Optimize AI Project Performance

Structure data representations more effectively to support AI initiatives and reduce failures associated with weak Data Architecture.

Improve AI and Machine Learning Workflows

Create more effective data representations that can support AI training, inference, and machine learning project performance.

Improve Data Quality

Apply techniques for evaluating and improving data quality, including the development of data quality scorecards.

Support Better Decision-Making

Understand how well-designed Data Models can make important information clearer and more useful for organizational decision-making.

Improve Performance and Scalability

Learn how Data Modeling can contribute to more efficient handling of large data volumes and better-performing applications.

Bridge Communication Gaps

Communicate data requirements more clearly between business stakeholders and technical implementation teams.

Standardize Data Understanding

Use Data Modeling to create more consistent representations of data across teams and organizational contexts.

Strengthen Data Integration and Migration

Apply stronger data requirements and representations when supporting complex system integrations and data migration initiatives.

Improve Business Intelligence

Use clearer data understanding and representation to support more effective Business Intelligence activities and informed decisions.

Understand New Business Domains Faster

Use Data Modeling techniques to develop a structured understanding of unfamiliar business domains and communicate that understanding more effectively.

Assess and Improve Data Models

Learn to evaluate Data Models for quality and incorporate considerations such as supportability and extensibility.

Prepare for Emerging AI Requirements

Understand the continuing role of Data Modeling and Data Architecture as AI technologies and organizational applications continue to evolve.

AI Data Modeling Masterclass

Reserve Your Place for the One-Day Masterclass

Develop practical Data Modeling skills that can support stronger AI initiatives, clearer business and technical communication, better data quality, and more effective data-intensive projects.

Date

October 13, 2026

Format

Distance Learning

Time

9:00 AM to 5:00 PM Eastern Time

Price

$899 USD

Prerequisites

None

Registration Form