Data modeling is an essential skill set for modern data management that has an important (but frequently unrecognized) role in artificial intelligence. Data modeling and artificial intelligence (AI) are both evolving fields. Everyone is aware of AI evolution because it is at the forefront of technology news. It seems that evolution of data modeling is a well-kept secret.  

AI models depend on data. Discriminative AI models classify existing data and use it to infer predictions and conclusions. Generative AI models create new data that is collected, stored, managed, and used as feedback. Modern data modeling provides knowledge and techniques needed to organize, understand, prepare, and manage data for artificial intelligence. Data models provide business context, describe data content and organization, support feature engineering and data preparation, and reinforce model interpretability.  

In this live, online, two-day training, Data Modeling for AI, instructor Dave Wells equips you with the knowledge and techniques to navigate the complex field of modern data modeling and artificial intelligence (AI), enabling you to implement sustainable solutions within your organization. Data modeling of the past was aligned with the design of relational databases. Today’s data modeling addresses many data types — relational, key-value, wide-column, document, graph, and more — at all levels from business semantics to design and implementation. This course will help successfully manage this new organizational reality. 

Two-Day Seminar Price: 

• $1,000 Early Bird Price through June 6, 2025 
• $1,200 after June 6, 2025 

Last day to register: Sunday, June 22, 2025 

Seminar CEUs: 9 
Seminar Date: Tuesday – Wednesday, June 24 - 25, 2025 
Seminar Time: 8 AM – 1 PM, Pacific Time / 11 AM – 4 PM, Eastern Time 

During the two days of this training, attendees will: 

• Learn data modeling essentials including what data modeling is, the processes involved, and how it functions as both a design and learning process. 
• Discuss data modeling levels of abstraction such as semantic, conceptual, logical, and physical data modeling necessary for building AI-based models. 
• Cover the various types of data models including semantic data models, subject area models, entity-relationship data models, dimensional data models, document data models, and graph data models. 
• Explore what AI is and the AI development lifecycle. 
• Learn about how business requirements and semantic data modeling, as well as data requirements and conceptual data modeling, are essential for understanding the business context and how it impacts AI success. 
• Discuss the importance of data sourcing, data acquisition, and data exploration in the context of data modeling and AI. 
• Focus on the role of data models in feature engineering, data preprocessing, and data transformation for AI. 
• Address the governance aspects of AI, ensuring that AI systems are developed and used responsibly. 
• Explore the importance of making AI models interpretable and explainable to ensure transparency and trust. 
• Discuss the challenges of data and AI biases, as well as the phenomenon of AI hallucination. 
• Explore the role of generative AI and large language models in data generation and their impact on AI development. 

Who Should Attend? 

This two-day, live, online seminar is intended for business and IT professionals at all levels, who have been tasked with understanding and implementing data modeling and AI on behalf of their organization. It assumes general business knowledge, but not specific technical knowledge or experience. It is appropriate for executives, departmental and/or project managers, data and enterprise architects, consultants, data scientists, BI professionals, and technical staff.  

The course is not designed for any specific business domain, and as such is applicable to any business function that is in need of more reliable AI and modeling processes, such as finance, manufacturing, human resources, analytics, operations, and more. During the breakout sessions different business domains will be discussed as examples. 

Group and team attendance is strongly encouraged because the workshop activities can be applied for your organization’s unique modeling and AI circumstances. Those activities produce results that have immediate application and lasting value for your ongoing modeling and AI efforts. 

We offer several bulk licensing options for corporate and group use. 

Contact us for a follow-up discussion! 

Seminar Format 

• A two-day workshop that includes lecture format over slides with questions either throughout or at the conclusion of each section, breakout sessions, and exercises. 
  • The seminar date is: Tuesday – Wednesday, June 24 -25, 2025 
  • Seminar time is: 8 AM – 1 PM, Pacific Time / 11 AM – 4 PM, Eastern Time 
• All seminar material will be made available for students to download. 
• DATAVERSITY will be integrating two platforms to run the training: The DATAVERSITY Training Center (DVTC) platform and Zoom. 
• The DVTC Platform is where you will start your training: https://training.dataversity.net 
  • This will be where you will log in, and then click a “Join Now” button on the day of the live training in your course dashboard. 
  • This platform will contain the syllabus for the day, information on navigating through both platforms, enable you to take notes throughout the training, join a forum with your classroom peers to network with each other even after the live online training is over, download materials, and access the recording of the training when it is complete. 
• When you click the “Join Now” button in the DVTC Platform, a Zoom window will open. 
  • This platform is where you will take the training, view the presentation, and engage in breakout sessions.