Batch ETL
Batch ETL (Extract, Transform, Load) is a data integration methodology where data is collected from various sources, processed in scheduled batches, and loaded into a target system like a data warehouse or database. It involves extracting data at regular intervals (e.g., daily or hourly), transforming it to meet business requirements (e.g., cleaning, aggregating), and loading it for analysis or reporting. This approach is commonly used for handling large volumes of data that don't require real-time processing.
Developers should learn Batch ETL when building data pipelines for business intelligence, analytics, or historical reporting, as it efficiently processes large datasets in bulk, reducing system load during off-peak hours. It's ideal for scenarios like nightly data warehouse updates, financial reporting, or compliance logging where data freshness isn't critical. Use it in enterprise environments with structured data sources like databases, logs, or files to support decision-making processes.