This article details the engineering behind a pipeline designed to consolidate data for Korean entertainment content, addressing the fragmentation across various sources and the lack of public APIs. It explains the choice of Supabase for its PostgreSQL-native features and free tier, alongside schema design decisions for movies, TV shows, cast, and streaming availability. The piece also covers the implementation of a data pipeline using Prefect and GitHub Actions to ensure reliable, scheduled updates to the database, including a specific solution for a PostgreSQL NULL constraint issue. AI
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IMPACT Provides a technical blueprint for managing and processing disparate data sources, relevant for data engineering in content-focused applications.
RANK_REASON The article describes the technical implementation of a data pipeline and database for a specific application, rather than a new product release or core AI research.