Extract, transform, and load (ETL) for Salesforce integration
Extracting data from the source systems. This typically involves data from several source systems, and both relational and non-relational structures.
Transforming the data to fit operational needs, which can also include data quality levels. The transform stage usually applies a series of rules or functions to the extracted data from the source to derive the data for loading into the end target(s).
Loading the data into the target system. The target system can vary widely from database, operational data store, data mart, data warehouse, or other operational systems.
Most mature ETL tools provide a change data capture capability. This capability is where the tool identifies records in the source system that have changed since the last extract, which reduces the amount of record processing.
Salesforce now also supports Change Data Capture which is the publishing of change events which represent changes to Salesforce records. With Change Data Capture, the client or external system receives near-real-time changes of Salesforce records in JSON format. This allows the client or external system to synchronize corresponding records in an external data store.










