Data integration is combining data from different sources into a consistent, unified view. Sources include applications, databases, files and partners, and the result serves people and systems alike.
An API (application programming interface) is a defined contract that lets one piece of software request data or actions from another. It hides internal details behind agreed operations, inputs and responses.
A data pipeline is an automated series of steps that moves data from where it is created to where it is stored, analysed or used. Steps along the way may extract, clean, reshape or enrich it.
ETL (extract, transform, load) cleans and reshapes data before loading it into a target system. ELT (extract, load, transform) loads raw data first and does the transformation inside the target, usually a warehouse.
Batch processing is handling data in scheduled groups, such as hourly or nightly runs, rather than processing each record the moment it arrives. Payroll runs, overnight warehouse loads and monthly billing are common examples, where completeness matters more than instant results.
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