In-Memory Business Intelligence: Concepts and Performance

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DC Field	Value	Language
dc.contributor.author	Rantung, V P	-
dc.contributor.author	Kembuan, O	-
dc.contributor.author	Rompas, Parabelem Tinno Dolf	-
dc.contributor.author	MEwengkang, A	-
dc.contributor.author	Liando, O	-
dc.contributor.author	Sumayku, J	-
dc.date.accessioned	2020-05-07T07:16:36Z	-
dc.date.available	2020-05-07T07:16:36Z	-
dc.date.issued	2018	-
dc.identifier.citation	ICIEVE 2017	en_US
dc.identifier.isbn	17578981, 1757899X	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/511	-
dc.description.abstract	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 Conference Series: Materials Science and Engineering	en_US
dc.relation.ispartofseries	IOP Conf. Series: Materials Science and Engineering 306(2018) 012129 doi:10.1088/1757-899X/306/1/012129;	-
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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FT Rompas KI 24 Prosiding In-Memory Business Intelligence-Concepts and Performance_compressed.pdf		1.2 MB	Adobe PDF	View/Open
FT Rompas PR 24 Prosiding In-Memory Business Intelligence-Concepts and Performance.pdf		1.69 MB	Adobe PDF	View/Open
Artikel 24.pdf	Similarity	1.21 MB	Adobe PDF	View/Open

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