ETL Processes
ETL (Extract, Transform, Load) is a data integration methodology used to collect data from various sources, transform it into a structured format, and load it into a target system such as a data warehouse or database. It involves extracting raw data from source systems, applying business rules and transformations (like cleaning, aggregating, or enriching), and loading the processed data into a destination for analysis or reporting. This process is fundamental in data engineering and business intelligence for ensuring data quality and accessibility.
Developers should learn ETL processes when working with data pipelines, data warehousing, or business intelligence projects, as it enables efficient data migration, integration, and preparation for analytics. It is crucial in scenarios like consolidating data from multiple databases, real-time data streaming for dashboards, or batch processing for historical analysis, helping organizations make data-driven decisions by providing clean, reliable data.