This blog post discusses the operationalization of data reliability at Grab through automated Data Production Issues (DPIs). It builds upon previous parts by introducing how Grab leverages its data mesh framework, specifically using tools such as Kinabalu and Hugo, to manage and resolve data quality issues in real-time. The author outlines the lifecycle of DPIs, from detection to resolution, and emphasizes the importance of automation in reducing operational downtime and enhancing trust in data products. The piece showcases Grab's commitment to maintaining data integrity and improving operational efficiency across its platforms.