Spring GDS 25th Anniversary
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Data pipeline
What is a data pipeline?
A data pipeline is the path data takes from where it is created to where it gets used. It pulls data from sources, moves it through any cleaning or reshaping it needs, and delivers it to a destination like a warehouse, a dashboard, or a machine learning model. Think of it as the wiring between systems that would otherwise never share anything.
Pipelines run in two main modes. Batch pipelines process data on a schedule, every hour or every night, which works for reporting that doesn't need to be live. Streaming pipelines process events as they happen, which matters when a fraud check or a live inventory count can't wait. A pipeline usually includes ingestion, transformation, and orchestration, the last being the layer that decides what runs when and what happens when a step fails. A subscription business might run a nightly batch pipeline that pulls payment events, joins them to account records, and lands a clean table its finance team queries every morning.
The term overlaps with ETL and ELT, which describe specific patterns inside a pipeline. A pipeline is the broader concept. It includes the failure handling, retries, monitoring, and scheduling that keep data flowing when a source goes down or a record arrives malformed.
Data pipelines at Dallonses
We design pipelines that survive contact with reality. Sources break. Schemas drift. A vendor changes an API without telling anyone. We build in the retries, alerts, and validation that catch these failures before they reach a dashboard and quietly corrupt a quarter of reporting.
Most of our pipeline work starts with a client whose data lives in too many places to trust. We map the real flow, decide where batch is enough and where streaming earns its complexity, and stand up something the client's own team can run and extend. Solid data analytics depends entirely on the layer underneath it, so we make that layer boring and dependable on purpose.
Need your data to move reliably between systems? Let's build the pipeline.
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