AI Data Pipelines: Architecture, Stages, and Orchestration

AI models require an architecture capable of processing data from multiple sources, rendering traditional ETL systems ineffective. AI data pipelines enable iterative model development, where data is ingested, cleaned, and models are continuously trained. This shift enhances organizations' ability to access real-time, actionable insights without compromising data quality.