How is a data pipeline defined?

A data pipeline is defined as a sequence of data processing steps that enable the efficient movement and transformation of data from one place to another. Each step in the pipeline can include data ingestion, transformation, validation, and storage, thus allowing for continuous data flow and processing.

The process starts with data ingestion, where raw data is collected from various sources. This data often goes through several stages of processing, which may include cleaning, transforming into a usable format, and enriching the data with additional insights. The final stage usually involves loading the processed data into a database or a data warehouse for analysis or business intelligence tasks.

This structured approach allows organizations to automate data processes, ensuring that data flows smoothly and is ready for analysis or application in real time. It enhances efficiency and reliability in managing data, which is critical for making data-driven decisions. Thus, the definition reflects the essence of a data pipeline as not merely a storage solution or a visualization method, but rather a comprehensive processing framework.