Data pipeline
An automated sequence of steps that moves data from sources to destinations and transforms it along the way, for example from an operational system into a warehouse and on to a report or model. Pipelines can run on a schedule or continuously.
Why it matters
Every dashboard, model and data-driven workflow depends on pipelines running correctly. Pipelines that fail silently, cannot be rerun safely or depend on one person’s knowledge are an operational risk.
Reliable pipelines are version-controlled, tested, monitored, rerunnable without creating duplicates, and documented with owners and downstream dependencies.
In practice
For example, a UK utilities contractor might run a pipeline every morning that pulls completed jobs from its field-service system, validates them, joins them to asset data and refreshes the operations dashboard, alerting the data team if any step fails.
Where Rodan fits
Rodan builds tested, observable pipelines through Data and Analytics Engineering.