The Data Analytics Pipeline
Once you understand the steps in a data analysis workflow, it's helpful to zoom out and see how those steps connect inside a real system.
That big-picture flow is called the data analytics pipeline.
What Is a Data Pipeline?
A data pipeline is the full journey that data takes from its original source to its final use in decision-making.
It includes the technical systems and tools that move, store, clean, and analyze the data.
In many real-world jobs, you won’t just analyze data — you’ll need to understand where it comes from, how it's processed, and who uses it next.
Key Stages of a Pipeline
Every pipeline is different, but most share a few key stages:
- Source: where the data comes from (e.g. forms, sensors, APIs)
- Storage: where it's held (e.g. databases, cloud services)
- Processing: cleaning, filtering, or formatting the data
- Analysis: applying logic or models to find patterns
- Visualization: turning results into dashboards or charts
- Action: using the output to make a decision
We’ll break these down visually in the next section using a whiteboard.
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