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 in data engineering for automating the flow of data from raw inputs to usable datasets, ensuring data quality, consistency, and reliability. ETL pipelines enable organizations to consolidate disparate data for business intelligence, reporting, and machine learning applications.
Developers should learn and use ETL pipelines when working with data-intensive applications, such as building data warehouses, performing data migrations, or supporting analytics platforms. They are essential in scenarios involving batch processing of large datasets, data cleaning, and integration from multiple sources like databases, APIs, or files. ETL pipelines help ensure data is accurate, timely, and accessible for decision-making, making them critical in industries like finance, healthcare, and e-commerce.