Extracting knowledge patterns in a data lake for management effectiveness

Extracting knowledge patterns in a data lake for management effectiveness

With the correlation collision between different types of data becomes more and more intense, a meaningful and far-reaching data revolution has arrived. Enterprises urgently require a hybrid data platform that can effectively break data silos, and unify data aggregation and sharing. Once the data la...

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Main Authors: Cheng Ziyi, Wang Haitong, Li Hongyan
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/74/e3sconf_ebldm2020_03045.pdf
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spelling doaj-7e5a40ecbc214894a5b60dbab70d803e2021-04-02T16:02:29ZengEDP SciencesE3S Web of Conferences2267-12422020-01-012140304510.1051/e3sconf/202021403045e3sconf_ebldm2020_03045Extracting knowledge patterns in a data lake for management effectivenessCheng Ziyi0Wang Haitong1Li Hongyan2International Business School, Shaanxi Normal UniversityInternational Business School, Shaanxi Normal UniversityInternational Business School, Shaanxi Normal UniversityWith the correlation collision between different types of data becomes more and more intense, a meaningful and far-reaching data revolution has arrived. Enterprises urgently require a hybrid data platform that can effectively break data silos, and unify data aggregation and sharing. Once the data lake was born, it has been a promising method for enterprises to profoundly improve their Business Intelligence. In this paper, we combine principle component analysis (PCA) with a network-based approach to extract a visual knowledge pattern from data sources in data lake, so as to improve management effectiveness.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/74/e3sconf_ebldm2020_03045.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Cheng Ziyi
Wang Haitong
Li Hongyan
spellingShingle Cheng Ziyi
Wang Haitong
Li Hongyan
Extracting knowledge patterns in a data lake for management effectiveness
E3S Web of Conferences
author_facet Cheng Ziyi
Wang Haitong
Li Hongyan
author_sort Cheng Ziyi
title Extracting knowledge patterns in a data lake for management effectiveness
title_short Extracting knowledge patterns in a data lake for management effectiveness
title_full Extracting knowledge patterns in a data lake for management effectiveness
title_fullStr Extracting knowledge patterns in a data lake for management effectiveness
title_full_unstemmed Extracting knowledge patterns in a data lake for management effectiveness
title_sort extracting knowledge patterns in a data lake for management effectiveness
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description With the correlation collision between different types of data becomes more and more intense, a meaningful and far-reaching data revolution has arrived. Enterprises urgently require a hybrid data platform that can effectively break data silos, and unify data aggregation and sharing. Once the data lake was born, it has been a promising method for enterprises to profoundly improve their Business Intelligence. In this paper, we combine principle component analysis (PCA) with a network-based approach to extract a visual knowledge pattern from data sources in data lake, so as to improve management effectiveness.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/74/e3sconf_ebldm2020_03045.pdf
work_keys_str_mv AT chengziyi extractingknowledgepatternsinadatalakeformanagementeffectiveness
AT wanghaitong extractingknowledgepatternsinadatalakeformanagementeffectiveness
AT lihongyan extractingknowledgepatternsinadatalakeformanagementeffectiveness
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