Lecture

The Data Analysis Workflow

Data analysis 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.


Why workflow matters

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.


What You'll Learn

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.

Quiz
0 / 1

In data analysis, it is recommended to use collected data exactly as it is.

True
False

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