Data Types and Their Characteristics

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What is qualitative data?

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Qualitative data refers to non-numerical information that describes qualities or characteristics, such as colours, textures or opinions.

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What is quantitative data?

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Quantitative data consists of numerical information that can be measured and analysed mathematically, such as height, weight or sales figures.

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Define structured data.

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Structured data is highly organised and stored in a predefined format, such as rows and columns in a database.

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What is semi-structured data?

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Semi-structured data is partially organised, containing elements of structured and unstructured data, such as JSON or XML files.

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What is unstructured data?

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Unstructured data is information that does not have a predefined format, such as emails, videos, audio files or social media posts.

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Give an example of qualitative data in a dataset.

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Customer feedback comments, such as "The service was excellent."

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Give an example of quantitative data in a dataset.

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The number of items sold in a shop each day, e.g., "50 items."

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What are key benefits of structured data?

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It is easy to search, store, and analyse using standard database tools.

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What challenges does unstructured data present?

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Unstructured data is difficult to organise, search, and analyse without specialised tools or machine learning techniques.

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What is metadata, and why is it important?

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Metadata is data about data, such as file size or creation date. It helps provide context and makes data easier to locate and organise.