Data - DoorDash Engineering Blog

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Data Using Metrics Layer to Standardize and Scale Experimentation at DoorDash

Learn how DoorDash build a metrics layer to enable consistent metrics and democratized decision making for experimentation

Arun Balasubramani

23 Minute Read

Data Machine Learning

Learn how we analyzed over 100K online delivery menus to develop menu best practices

Finn Qiao 14 Minute Read

DoorDash engineering explains how to edit large data tables safely and quickly in a production database.

Justin Lee 12 Minute Read

Data Machine Learning

To speed up the development of new features we needed a way to increase our experiment capacity. Learn how we improved it by 4X

Jessica Zhang

Yixin Tang 13 Minute Read

Backend Data

Learn how moving ML models to a prediction service can free up RAM and CPU for more scalable development

Sarah Chen 11 Minute Read

Data Machine Learning

Learn the challenges and best practices to successfully growing a data platform organization

Sudhir Tonse 26 Minute Read

Data Machine Learning

DoorDash engineers built Curie, a new experimentation analysis platform, to better gauge the success of product experiments.

Arun Balasubramani 10 Minute Read

Backend Data Machine Learning

Learn the challenges of reducing network overheads with gRPC optimizations

ArbazKhan 17 Minute Read

Data Machine Learning

Learn how building a prediction service enables the utilization of ML models based on real-time data

Cody Zeng 11 Minute Read