Big Data
Last Updated: July 29, 2026 | By Mihail Sebastian | AI Dictionary
Extremely large, fast, or varied datasets that conventional processing tools cannot handle, usually described by the three Vs: volume, velocity, and variety.
What is Big Data?
Big data is data too large, too fast-moving, or too varied for conventional databases and processing tools to handle. The usual shorthand is the three Vs: volume, velocity, and variety, sometimes joined by veracity and value.
The label matters less than the consequence: at this scale, storing, processing, and checking data all require different tools, from distributed storage to frameworks like Spark. Big data is also the raw material of modern machine learning, which needs large training sets to perform well.
Types of Big Data
- Structured data follows a fixed format, like the rows and columns of a database table or a spreadsheet.
- Unstructured data has no predefined format: images, video, audio, free text, social media posts.
- Semi-structured data sits between the two, carrying some organization without a rigid schema; JSON and XML files are the standard examples.
Most of the world’s data is unstructured. That is one reason big data and AI grew up together: neural networks are the first tools that extract value from images and free text at scale.
Example of Big Data
A payment card network is big data in all three dimensions at once. Volume: billions of stored transactions. Velocity: thousands of new ones arriving every second, each needing a fraud decision in milliseconds. Variety: transaction amounts sit next to merchant categories, device fingerprints, and location signals.
No single database server can score every incoming transaction against years of history in real time, so the network splits the work across clusters of machines. Its fraud models are trained on that accumulated history – the scale that makes the problem hard is the same scale that makes detection possible.
Related AI terms: Data Analytics · Data Mining · Data Quality · Machine Learning · Spark
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Mihail Sebastian — Writes about AI governance, regulation, and the technology behind them. Placeholder bio — replace with a real credential line. About