AI Data Modeling One-Day Masterclass

Are you ready to supercharge your artificial intelligence (AI) projects with expert-level data modeling skills? Join us for an intensive, one-day Masterclass on Data Modeling for Artificial Intelligence!

What You'll Learn

In this comprehensive workshop, you'll dive deep into:

• Fundamentals of AI-Driven Data Modeling: Discover how to structure data for optimal AI performance.

• Learn about the three models: stakeholder models and technology-enabling models that represent your organization’s Data DNA.

• Practice these methods and techniques under the guidance of a world-renowned practitioner.

Why Attend?

• Boost AI project success by reducing costly failures due to poor Data and Data Architecture.

• Enhance Communication by bridging the gap between business data understanding and requirements and technical implementation.

• Apply your learning through practical exercises – not quizzes!

• Understand and prevent AI “hallucinations” and fabrications.

• Recognize the danger in the use of “public large language models”

Distance Learning Tuesday, July 8, 2025

• Central Daylight Time | UTC -5 | 8:00 AM - 5:00 PM

Distance Learning Thursday, July 10, 2025

• Central European Time | UTC +2 | 8:00 AM - 5:00 PM

Who Should Attend?

• Data Scientists

• Business Stakeholders

• AI Engineers

• Business Analysts

• IT Professionals

• Anyone involved in AI and machine learning projects

Educational Resources

Presentation Materials:  Attendees will receive copies of presentation slides from the Masterclass, allowing you to revisit the content after the session.

Ongoing Support

Coaching Sessions: As hands-on practitioners, we offer one-on-one follow-up sessions or remote calls, that can help you apply what you learned and address specific challenges you face.

Enhanced AI Project Success

- Optimized Data Structures: Learn how to structure data for optimal AI performance, preventing costly failures due to poor data architecture.

- Improved AI & ML Training: Discover advanced data modeling techniques to refine AI and machine learning training, enhancing your projects' outcomes.

Strategic Advantages

- Decision-Making Support Gain insights into how well-designed data models provide valuable information for informed decision-making processes.

- Performance Optimization: Understand how proper data modeling leads to faster application performance and more efficient handling of large data volumes.

Industry Insights

-Real-World Applications: Explore practical methods to assess the strategic impacts of data modeling in AI contexts.

- Future Trends: Get insights into the future of AI and how data modeling plays a crucial role in emerging technologies.

Collaboration and Communication

- Bridge Business and Technical Gaps: Learn to effectively communicate data requirements between business stakeholders and technical teams.

- Standardization: Understand how data modeling promotes consistency in data representation across the organization.

1. Optimize AI Project Performance: Attendees will be able to structure data representation for optimal AI performance, preventing costly failures due to poor data architecture.

2. Enhance Machine Learning Workflows: Attendees can create efficient data representations that accelerate AI training and inference, improving the overall effectiveness of machine learning projects.

3. Improve Data Quality: Participants will be able to develop data quality scorecards, ensuring AI models work with clean, high-quality data.

4. Bridge Communication Gaps: New skills will enable attendees to effectively communicate data requirements between business stakeholders and technical teams, facilitating better project outcomes.

6. Apply Best Practices: Participants can incorporate supportability and extensibility features into their data models and assess the quality of any data model. Best practices are not on the public internet – they are in this Masterclass.

7. Streamline Business Intelligence: The skills gained can be applied to improve business intelligence processes, leading to more informed decision-making.

8. Enhance Data Integration Projects: Be better equipped to define requirements for complex projects like system integrations and data migrations.

9. Quickly Understand New Domains: The data modeling techniques learned will enable attendees to rapidly grasp new business domains and effectively communicate about the data.