Data modelling to support data product delivery using GenAI

Join an exclusive peer discussion for senior data and AI leaders.

This small-group session offers a confidential space for senior professionals to exchange insights, share challenges, and learn from one another. While the session is designed exclusively for DataIQ clients, we occasionally welcome select guests who bring valuable perspectives to the conversation.

DataIQ clients: Please secure your place via the DataIQ Hub.

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Questions:  

  1. How are organisations executing logical to physical data modelling to support the delivery of data products?
  2. How are GenAI tools being used to accelerate data modelling that was historically done by data architects and data modellers?
  3. How does moving from data lakes and large data dumps to structured, modelled data products change the way data modelling is approached?

Who should attend?

This session is designed for data and AI leaders who:
  • Work in large, complex, high-maturity organisations operating in regulated environments and;
  • Are directly involved in delivering data products and have experience with data modelling.

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Accelerator format:

These are 60-minute panel discussion type events, that allow up to 10 participants to work through a set of questions from the host participant. We curate every panel to ensure the right working group is in place to provide ideas, suggestions and perspectives towards the case. 

In each session you can expect:

  • Prequalified group of experts in the area
  • A round of introductions to each participant (up to 10 people)
  • An in-depth discussion with inputs from cross-industry participants
  • Concrete take-aways and action plan for moving forward

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How to apply if you are not a client:

If you are currently not subscribed to the DataIQ service, but would like to join this session, you can apply to be considered for participation by filling in the form below.

DataIQ clients: Please secure your place via the DataIQ Hub.

Request attendance

Local Time

  • Timezone: America/New_York
  • Date: 28 May 2026
  • Time: 10:00am - 11:00am