Data pipeline
A series of connected processing stages that move data from one or more sources to a destination, transforming and validating it along the way.
In more detail
A data pipeline is the path data travels from where it originates to where it is used, passing through stages that extract it, clean it, transform it, and load it into a destination such as a warehouse. Each stage depends on the ones before it, which is why pipelines are often modeled as a directed acyclic graph of steps.
Pipelines are the backbone of analytics and reporting, since the numbers a business relies on are only as trustworthy as the pipeline that produced them. A stage that silently drops rows, mishandles a format, or fails without notice corrupts everything downstream, which is why validation and observability matter as much as the transformation itself.
Where this shows up at Ceven
Ceven can build the data-moving parts of a process into a workflow, gathering, transforming, and delivering data across the connected tools, with AI steps for the judgment a rigid pipeline cannot express. Because every stage is recorded in the audit trail, a pipeline built this way is observable rather than a black box that quietly drops data.