Data Integration platforms (ETL and ELT) extract data from source systems — SaaS applications, operational databases, event streams, files — and load it into analytical stores (warehouses, lakehouses, or data lakes), with transformations applied either before loading (ETL) or after loading in the destination (ELT). Core capabilities include a library of pre-built source connectors, change-data-capture (CDC) for databases, incremental and full-refresh sync modes, schema evolution handling, streaming and batch ingestion, destination-agnostic loading, and pipeline observability. The modern-stack default is ELT with transformation handled separately in the warehouse by dbt-class tools. Leading vendors include Fivetran (with dbt Labs), Airbyte, Matillion, Stitch, Qlik (Talend), Informatica, Azure Data Factory, and AWS Glue.