Data teams have long started with a data-first approach: extract production data, explore it, and discover potential use cases. This method encourages creativity and quick experimentation but often leads to unclear ownership and mismatched expectations between producers and consumers.

A newer contract-first approach, supported by data contracts, starts differently. Teams first discuss data requirements with business users, define expectations and metadata through data contracts, and only then implement the data product. This promotes better collaboration, transparency, and quality assurance through contract-driven testing.

Both approaches have their place. In this talk, we explore how to combine them effectively: using data-first exploration to uncover opportunities and contract-first principles to ensure trust, clarity, and long-term reliability. We will discuss how this balance reshapes requirements engineering, improves metadata quality, and drives a lasting cultural shift toward shared responsibility in data ecosystems.