Data Modeling Techniques Used for Big Data in Enterprise Networks

dc.contributor.authorOmollo, Richard
dc.contributor.authorAlago, Sabina
dc.date.accessioned2021-03-29T12:32:51Z
dc.date.available2021-03-29T12:32:51Z
dc.date.issued2020-04-20
dc.description.abstractThe deployment and maintenance of enterprise networks form the bedrock of any organization, be it government, commercial, academic, and/or non-profit making. These networks host vast amounts of information, databases, in either temporary mode while in transit or permanent mode while stationary. The databases are managed by the information systems with appropriate functions that meet consumers’ needs. Databases hold varying data – structured, semi structured, or unstructured. Data is increasingly becoming a vital organizational asset and therefore plays a crucial role in making organizational decisions. With growth in the internet, digital data sources have become ubiquitous. In turn, this has seen the continued growth in the volume, variety, veracity, velocity, and value of data. Big data brings with its data complexities that have an eventual impact on the data modeling techniques. This paper presents a review of big data modeling techniques with a concentration of enterprise networks. We started by appreciating big data before embarking on modeling techniques for big data.en_US
dc.identifier.issn2394-5443 (Print)
dc.identifier.issn2394-7454 (online)
dc.identifier.urihttp://ir.jooust.ac.ke:8080/xmlui/handle/123456789/9270
dc.language.isoenen_US
dc.publisherInternational Journal of Advanced Technology and Engineering Explorationen_US
dc.subjectKeywords Dataen_US
dc.subjectModelen_US
dc.subjectModeling techniquesen_US
dc.subjectBig dataen_US
dc.subjectEnterprise networksen_US
dc.subjectDatabasesen_US
dc.titleData Modeling Techniques Used for Big Data in Enterprise Networksen_US
dc.typeArticleen_US

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