Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/1478
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | T, Saranya | - |
dc.contributor.author | D, Nivetha | - |
dc.date.accessioned | 2020-09-15T04:49:06Z | - |
dc.date.available | 2020-09-15T04:49:06Z | - |
dc.date.issued | 2018 | - |
dc.identifier.issn | 2250-3021 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/1478 | - |
dc.description.abstract | Big data is a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage, and process the data with low-latency. And it has one or more of the following characteristics – high volume, high velocity, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media - much of it generated in real time and in a very large scale. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Sri Sankara Arts and Science College | en_US |
dc.subject | big data | en_US |
dc.subject | black box data | en_US |
dc.subject | social media data | en_US |
dc.subject | stock exchange data | en_US |
dc.subject | power grid data | en_US |
dc.subject | transport data | en_US |
dc.subject | search engine data | en_US |
dc.title | BIG DATA | en_US |
dc.title.alternative | Computational intelligence and data science | en_US |
dc.type | Book | en_US |
Appears in Collections: | International Conference |
Files in This Item:
File | Description | Size | Format | |
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BIG DATA.docx | 10.14 kB | Microsoft Word XML | View/Open |
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