A data pipeline is an automated series of processes that move and transform data from one location to another. It can involve various operations, such as extracting data from different sources, transforming it to ensure quality and consistency, and loading it into a destination like a data warehouse. Data pipelines are essential for managing the flow of data in organizations, enabling them to make informed decisions based on accurate and timely information.

There are different types of data pipelines, including ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). ETL pipelines extract data, clean it, and then load it into a repository, while ELT pipelines load the data first and then transform it. Both types serve to streamline data processing and ensure that data is ready for analysis or reporting ¹².

Data pipelines can also vary in complexity, from simple workflows to more intricate systems that handle real-time data streaming. They are crucial for ensuring data availability and integrity across various applications and analytics platforms ³⁵.