Machine Learning Resources

Distinguish between Structured and Unstructured Data

Structured data refers to data that has a clear and pre-defined schema, allowing it to be easily understood by both humans and machines. Structured data provides a clear, organized and standardized way of representing information, making it possible for computers to process, analyze and draw insights from it. Some common examples of structured data formats include CSV (Comma-Separated Values), JSON (JavaScript Object Notation), and XML (eXtensible Markup Language).

Unstructured data on the other hand, refers to information that is not organized in a pre-defined format and is typically more difficult for computers to process and analyze. This makes it challenging to extract insights and information from it. Unstructured data is more free-form and can include a wide variety of data types, such as text, images, audio, and video.

The following table compares and contrasts structured data from unstructured data:

Structured DataUnstructured Data
StructurePre-defined schemaNo pre-defined schema
FormatText and NumbersWide variety of formats including text, images, video, sound, etc.
StorageRelational Databases and WarehousesNoSQL Databases and Datalakes
InsightsEasy to search, query and analyzeDifficult to analyze
ProcurementDifficult and time-consuming to procureEasy to Procure
ExamplesSensor Data
Financial Data
Internet Forms
Internet blogs and websites
Phone Calls
Difference between Structured and Unstructured Data

Video Explanation

The following video provides a nice overview of Structured and Unstructured data, and also compares the two (Runtime: 7 mins)

Structured vs Unstructured Data

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