Data Pipelines
Data pipelines are automated processes that move and transform data from various sources to a destination, such as a data warehouse or analytics platform, enabling efficient data processing and analysis. They typically involve stages like extraction, transformation, loading (ETL), or extraction, loading, transformation (ELT), and are essential for handling large-scale, real-time, or batch data workflows in modern data-driven applications.
Developers should learn data pipelines to build scalable systems for data ingestion, processing, and integration, which are critical in domains like big data analytics, machine learning, and business intelligence. Use cases include aggregating logs from multiple services, preparing datasets for AI models, or syncing customer data across platforms to support decision-making and automation.