Data mesh at Grab part I: Building trust through certification

This post details the implementation of data certification as a cornerstone of Grab's data mesh. It introduces the concepts of data contracts, defining SLAs for schema, data quality, and freshness, and establishes ownership roles (Business Data Owners, Technical Data Owners). A key technical contribution is the automated Data Production Incident (DPI) system, which creates tickets for breached data contracts based on automated data quality tests (availability, timeliness, consistency, completeness, accuracy, validity). The post also highlights the operationalization strategy, including executive buy-in, organization-wide reporting, and dashboards to guide teams on certifying high-usage tables, with a north star metric of 'percentage of queries hitting certified assets'. Outcomes include 75% of queries hitting certified assets, a 400% YoY increase in deprecated assets, and a 58% reduction in P80 datasets.
More from the Data Production Issue (DPI) Operationalization trail
- Data Mesh at Grab (Part III): Operationalizing data reliability with automated DPIs
- The Hugo evolution: Engineering Grab's unified, one-click data ingestion platform with Apache Flink
- Data Mesh at Grab (Part II): The foundational tools behind certification
- Real-time data quality monitoring: Kafka stream contracts with syntactic and semantic test
- The complete stream processing journey on FlinkSQL