ELTP: Extending ELT for Modern AI and Analytics

The ELTP architecture (Extract, Load, Transform, Publish) is introduced as a solution to common design mistakes made when building data pipelines for AI, analytics, or data engineering. Unlike the traditional ETL approach, ELTP separates replication and processing steps, making it more stable and scalable. It also addresses the gap in delivering data to downstream users and systems by adding a 'Publish' step. The Publish framing is a simple way to describe how transformed data can be efficiently delivered to various destinations such as external SaaS applications, file stores, CRM systems, AI vector stores, and other databases. ELTP offers benefits like sending data files to external systems, decentralizing analytic queries, and publishing to downstream applications and indexes.