Scaling analytics in a startup requires a cost-effective, open-source approach. In this talk, I’ll break down how we built a scalable, automated data pipeline using Airbyte, dbt, and Airflow to process and deliver insights efficiently. We extract data from various sources using Airbyte OSS, transform and model it in dbt, and orchestrate everything with Airflow—ensuring stakeholders receive timely insights via Metabase dashboards and Slack alerts.

Attendees will learn:

How to set up an open-source ELT pipeline with Airbyte and dbt
Best practices for data modeling to enable self-service analytics
How to automate workflows and manage dependencies with Airflow
Real-world challenges and how we optimized performance

This talk is ideal for teams looking to move from ad-hoc analysis to structured, automated analytics workflows.