A data pipeline consists of a set of processes that handle the extraction, transformation, and loading (ETL) of data from various sources to a destination, such as a data warehouse or data lake. The pipeline automates data collection, cleansing, transformation, and integration to ensure that data is available for analysis and reporting. It typically includes stages like data ingestion, data processing, data storage, and data delivery. Data pipelines are essential for maintaining data flow efficiency, ensuring data quality, and enabling timely insights across systems. They can be designed to handle batch processing or real-time data streams, depending on the requirements of the organization.