Lecture

Types of Data: Structured vs Unstructured

Not all data looks the same—and its structure directly affects how you analyze it.

Before starting any project, ask yourself: What type of data am I working with?

Some data is neatly organized and easy to process, while other data is free-form and context-heavy. Each type requires different tools, storage, and cleaning methods.


Data Analysis Workflow

As a data analyst, you'll often need to:

  • Choose the right format to store or query data
  • Understand what cleaning steps are needed
  • Select tools based on the data structure

Recognizing whether your data is structured or unstructured helps you think ahead, avoid pitfalls, and select the right approach.

You’ll explore the characteristics and real-world examples of each data type in the slides.

Quiz
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What is a key characteristic of structured data compared to unstructured data?

It is deeply contextual and requires complex processing techniques.

It consists of free-form data that is difficult to organize.

It is highly organized and easy to sort.

It requires advanced video processing tools.

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