"In an AI-driven research world, synthetic data is only as strong as the population data that grounds it. Through a case study focused on the Americas, this session shows how boosting census strength improves model quality and predictive performance, while also revealing what is at stake when representation is weak, uneven, or missing. Attendees will gain a practical framework for thinking about census-based synthetic modelling not just as a technical exercise, but as a competitive advantage for smarter, more trustworthy decisions.
Three key takeaways:
1. The link between census strength, representativeness, and predictive accuracy.
2. How to use synthetic data more responsibly and effectively in insights work.
3. A practical lens for evaluating model trustworthiness, risk, and business relevance."
