Big data: Difference between revisions
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For example, anti-fraud technology in banks can analyse how often bank customers log into their account, where they usually log in from, and how quickly they type in their user name and password. | For example, anti-fraud technology in banks can analyse how often bank customers log into their account, where they usually log in from, and how quickly they type in their user name and password. | ||
This process is also known as ''data mining'', or ''knowledge discovery in data''. | This process is also known as ''data mining'', or ''knowledge discovery in data''. | ||
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== See also == | == See also == | ||
* [[Data]] | |||
*[[Data mining]] | *[[Data mining]] | ||
*[[Data science]] | |||
* [[Database]] | |||
* [[Datasphere]] | |||
*[[General Data Protection Regulation]] | *[[General Data Protection Regulation]] | ||
*[[Granular]] | *[[Granular]] | ||
Latest revision as of 20:50, 13 August 2022
Big data refers to the large volumes of historically unstructured information held by organisations.
Big data technology interrogates this previously unstructured information to produce more useful summarised and selected data and analysis.
For example, anti-fraud technology in banks can analyse how often bank customers log into their account, where they usually log in from, and how quickly they type in their user name and password.
This process is also known as data mining, or knowledge discovery in data.
