As organisations invest heavily in data platforms and AI, many still struggle to translate data into measurable business outcomes. The key is not more data – it’s better data products. This session explores a practical framework for designing data products that deliver real value by focusing on four essential pillars.

First, every data product must begin with clear business intent, ensuring that development is driven by specific decisions, outcomes, and measurable impact. Second, data products must be grounded in enterprise truth, aligning with trusted, governed sources so teams operate from a shared understanding of critical data. Third, organisations must prioritise reuse before create, enabling teams to discover and build upon existing data assets rather than duplicating effort and introducing inconsistency. Finally, effective data products are governed by design, embedding policies, quality, and lineage directly into the product lifecycle rather than retrofitting governance after the fact.

Through real-world examples and practical guidance, this session will show how these four pillars enable organisations to deliver scalable, trusted, and reusable data products that accelerate analytics, AI, and decision-making across the enterprise.