Overview
A data pipeline refers to the various steps data needs to go through in order to be processed, transformed, and stored in data warehouses or data lakes for business intelligence and analytics. The data pipeline process includes data ingestion, data processing, storage, analysis, and visualization. With each step of the data pipeline process, data needs to be transferred between different systems and applications. Instead of having data engineers spend time on these manual tasks, an automated data pipeline does this automatically. This helps boost productivity, improves data quality, provides more valuable insights, and simplifies the entire data pipeline process. With automated data pipelines, it’s easier for organizations to manage data at scale.
