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The structure, or lack thereof, of data

When given a new dataset, it is first important to recognize whether or not your data is structured or unstructured:

  • Structured (organized) data: Data that can be broken down into observations and characteristics. They are generally organized using a tabular method (where rows are observations and columns are characteristics).

  • Unstructured (unorganized) data: Data that exists as a free-flowing entity and does not follow standard organizational hierarchy such as tabularity. Often, unstructured data appears to us as a blob of data, or as a single characteristic (column).

A few examples that highlight the difference between structured and unstructured data are as follows:

  • Data that exists in a raw free-text form, including server logs and tweets, are unstructured

  • Meteorological data, as reported by scientific instruments in precise movements, would be considered highly structured as they exist in a tabular row/column structure

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