The Data Analysis Workflow

Data analytics isn’t just about numbers — it’s about moving from raw input to useful insight.

To do that, analysts follow a structured process.
This helps avoid messy guesswork and makes results easier to replicate and explain.

Without a clear process, it’s easy to:

• Miss important issues in the data
• Draw incorrect conclusions
• Waste time fixing preventable mistakes
• Lose the trust of your team or client

A good workflow brings structure to your thinking and allows you to communicate your process clearly to others.

In this course, we’ll guide you through each major step:

1. Ask a Question – What are we trying to learn or solve?
2. Collect Data – Where can we get reliable data?
3. Clean the Data – Fix inconsistencies, missing values, and errors
4. Analyze the Data – Explore patterns and test hypotheses
5. Visualize and Share – Turn findings into clear, impactful visuals

These stages form the core loop of real-world analytics.
In the next section, you’ll see this process mapped visually.