ETL
ETL (Extract, Transform, Load) is a data integration process that involves extracting data from various sources, transforming it into a structured format, and loading it into a target system such as a data warehouse or database. It is a foundational concept in data engineering and business intelligence for consolidating and preparing data for analysis. The process ensures data quality, consistency, and accessibility across an organization.
Developers should learn ETL when working with data pipelines, data warehousing, or analytics projects, as it enables efficient data movement and processing from disparate sources. It is essential for scenarios like migrating data to cloud platforms, building real-time dashboards, or integrating legacy systems, helping to automate workflows and support data-driven decision-making. Mastery of ETL is crucial for roles in data engineering, business intelligence, and big data applications.