In-Memory Business Intelligence: Concepts and Performance

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DC Field	Value	Language
dc.contributor.author	Rantung, Vivi Peggie	-
dc.contributor.author	Kembuan, Olivia	-
dc.contributor.author	Rompas, Parabelem Tinno Dolf	-
dc.contributor.author	Mewengkang, Alfrina	-
dc.contributor.author	Liando, Olivia Eunike Selvie	-
dc.contributor.author	Sumayku, James	-
dc.date.accessioned	2018-03-21T00:56:47Z	-
dc.date.available	2018-03-21T00:56:47Z	-
dc.date.issued	2018-02-22	-
dc.identifier.citation	V P Rantung et al 2018 IOP Conf. Ser.: Mater. Sci. Eng. 306 012129	en_US
dc.identifier.other	doi:10.1088/1757-899X/306/1/012129	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/33	-
dc.description.abstract	This research aims to discuss in-memory Business Intelligent (BI) and to model the business analysis questions to know the performance of the in-memory BI. By using, the Qlickview application found BI dashboards that easily accessed and modified. The dashboards are developed together using an agile development approach such as pre-study, planning, iterative execution, implementation, and evaluation. At the end, this research helping analyzer in choosing a right implementation for BI solution.	en_US
dc.language.iso	en	en_US
dc.publisher	IOP Publishing Ltd	en_US
dc.relation.ispartofseries	IOP Conf. Series: Materials Science and Engineering;306	-
dc.title	In-Memory Business Intelligence: Concepts and Performance	en_US
dc.type	Article	en_US
Appears in Collections:	Lecturer Scientific Papers

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