Analysis of Data Warehouse Architectures: Modeling and Classification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00109110" target="_blank" >RIV/00216224:14330/19:00109110 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5220/0007728006040611" target="_blank" >http://dx.doi.org/10.5220/0007728006040611</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0007728006040611" target="_blank" >10.5220/0007728006040611</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of Data Warehouse Architectures: Modeling and Classification

Popis výsledku v původním jazyce

With decades of development and innovation, data warehouses and their architectures have been extended to a variety of derivatives in various environments to achieve different organisations’ requirements. Although there are some ad-hoc studies on data warehouse architecture (DWHA) investigations and classifications, limited research is relevant to systematically model and classify DWHAs. Especially in the big data era, data is generated explosively. More emerging architectures and technologies are leveraged to manipulate and manage big data in this domain. It is therefore valuable to revisit and investigate DWHAs with new innovations. In this paper, we collect 116 publications and model 73 disparate DWHAs using Archimate, then 9 representative DWHAs are identified and summarised into a”big picture”. Furthermore, it proposes a new classification model sticking to state-of-the-art DWHAs. This model can guide researchers and practitioners to identify, analyse and compare differences and trends of DWHAs from componental and architectural perspectives.

Název v anglickém jazyce

Analysis of Data Warehouse Architectures: Modeling and Classification

Popis výsledku anglicky

With decades of development and innovation, data warehouses and their architectures have been extended to a variety of derivatives in various environments to achieve different organisations’ requirements. Although there are some ad-hoc studies on data warehouse architecture (DWHA) investigations and classifications, limited research is relevant to systematically model and classify DWHAs. Especially in the big data era, data is generated explosively. More emerging architectures and technologies are leveraged to manipulate and manage big data in this domain. It is therefore valuable to revisit and investigate DWHAs with new innovations. In this paper, we collect 116 publications and model 73 disparate DWHAs using Archimate, then 9 representative DWHAs are identified and summarised into a”big picture”. Furthermore, it proposes a new classification model sticking to state-of-the-art DWHAs. This model can guide researchers and practitioners to identify, analyse and compare differences and trends of DWHAs from componental and architectural perspectives.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 21st International Conference on Enterprise Information Systems

ISBN

9789897583728

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

604-611

Název nakladatele

SciTePress

Místo vydání

Crete, Greece

Místo konání akce

Crete, Greece

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000570422800062