As the amount of data Grab handles grows, there is an increased need for quick detections for data anomalies (incompleteness or inaccuracy), while keeping it secure. Read this to learn how the Risk Data team utilised Flink and Datadog to enhance data observability within Grab’s services.

Explore how the GrabX Decision Engine, an integral part of Grab's Experimentation platform, streamlines the testing of thousands of experimental variants weekly. This blog delves into how this internally open-sourced package institutionalises best practices in experimental efficiency and analytics, thereby ensuring accurate and reliable conclusions from each experiment.

With cross-platform monitoring, a common problem is the difficulty in getting comprehensive and in-depth views on metrics, making it tough to see the big picture. Read to find out how the Data Tech team ideated Iris to turn observations into actionable insights for enhanced decision-making.

With the size of our app growing to include more features, Grab recognised it as a potential hurdle for new users with small storage capacities or restricted Internet bandwidth. Read to find out more about Project Bonsai and how it reduced app download size and app disk size.

As the data lake landscape matures over the years, it presents opportunities to unlock more business value from the data. This correlates with the increased demand for flexible ad-hoc usage of fresh data. This article explores how we implemented data ingestion in Hudi table formats using Flink to meet this business demand.

The Grab superapp offers a comprehensive array of services from ride-hailing and food delivery to financial services. This creates multifaceted user journeys, covering homepages, product pages, checkouts, and interactions with diverse content, including advertisements and promo codes. Read this to find out more.

Understand how Grab employs a combination of automated and manual content moderation to manage its dynamic marketplace content efficiently, while also collaborating with Google to ensure marketplace safety.

As Grab matures along the digitalisation journey, it is collecting and streaming event data generated from the end users of its superapp on a larger magnitude than before. Coban, Grab’s data-streaming platform team, is looking to help unlock the value of streaming data at an earlier stage of the data journey before this data is typically stored in a central location (“Data Lake”). This allows Grab to serve its superapp users more efficiently.