ETL Pipelines
ETL (Extract, Transform, Load) Pipelines are a data integration process that extracts data from various sources, transforms it into a structured format suitable for analysis or storage, and loads it into a target system such as a data warehouse or database. They are fundamental for consolidating disparate data, ensuring data quality, and enabling business intelligence and analytics. Modern ETL pipelines often handle large volumes of data in batch or real-time, supporting data-driven decision-making in organizations.
Developers should learn and use ETL Pipelines when building data infrastructure for applications that require data aggregation from multiple sources, such as in business analytics, reporting, or machine learning projects. They are essential for scenarios like migrating legacy data to new systems, creating data warehouses for historical analysis, or processing streaming data from IoT devices. ETL skills are critical in roles involving data engineering, as they ensure reliable, clean, and accessible data for downstream processes.