AI Glossary
Data Pipeline
A system that collects, transforms, and moves data between different locations and applications.
Data Pipeline
Overview
Data rarely stays in one place.
Organizations constantly move information between databases, applications, analytics platforms, cloud systems, and AI tools.
This movement is often managed through a data pipeline.
A data pipeline is a series of processes that collect, transform, and transfer information from one system to another.
A helpful way to think about a data pipeline is a transportation network.
Just as roads move people and goods between locations, data pipelines move information between systems.
Some pipelines simply transfer data.
Others clean, organize, and transform information before it reaches its destination.
Data pipelines are critical because AI systems depend on having access to accurate and timely information.
If information is incomplete, outdated, or corrupted, AI performance may suffer.
As organizations continue adopting AI, reliable data pipelines are becoming an increasingly important part of modern data infrastructure.
Why It Matters
Data pipelines help ensure information reaches AI systems efficiently and accurately.
Real-World Example
An online retailer may use a data pipeline to move customer purchase information from sales systems into analytics platforms.