Current data architectures often lack expectations, autonomy, and reliability because data generators are often unaware of how their data is used downstream.
These are data quality tests codified into the ingestion pipeline. They fail fast, alerting engineers immediately rather than allowing corrupt data to pollute the warehouse. Current data architectures often lack expectations
One of the biggest killers of data quality is unplanned breaking changes. A contract mandates versioning. If a producer needs to change a column type, they must create a new version of the contract. This signals to consumers that a change is coming, allowing them to update their queries before the new data arrives. This synchronization prevents downtime and data errors. Current data architectures often lack expectations