Developing Reliable Taxonomic Features for Data Warehouse Architectures

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00115621" target="_blank" >RIV/00216224:14330/20:00115621 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/CBI49978.2020.00033" target="_blank" >http://dx.doi.org/10.1109/CBI49978.2020.00033</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CBI49978.2020.00033" target="_blank" >10.1109/CBI49978.2020.00033</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Developing Reliable Taxonomic Features for Data Warehouse Architectures

Popis výsledku v původním jazyce

Since there is a large variety of data warehouse architectures with different structures and components, it is very difficult and time-consuming to systematically analyse them and obtain insights from those architectures. One effective way to understand those architectures is using a taxonomy to classify them. However, most of the taxonomic features are derived in an ad-hoc way and the reliability of those features is unknown. This paper therefore is to develop a set of reliable features by modeling different data warehouse architectures and further generate the structural knowledge represented by a taxonomy. This taxonomy is further validated by evaluating two real-world data warehouse architectures from IBM and Facebook.

Název v anglickém jazyce

Developing Reliable Taxonomic Features for Data Warehouse Architectures

Popis výsledku anglicky

Since there is a large variety of data warehouse architectures with different structures and components, it is very difficult and time-consuming to systematically analyse them and obtain insights from those architectures. One effective way to understand those architectures is using a taxonomy to classify them. However, most of the taxonomic features are derived in an ad-hoc way and the reliability of those features is unknown. This paper therefore is to develop a set of reliable features by modeling different data warehouse architectures and further generate the structural knowledge represented by a taxonomy. This taxonomy is further validated by evaluating two real-world data warehouse architectures from IBM and Facebook.

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

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 22nd IEEE International Conference on Business Informatics - CBI 2020

ISBN

9781728199269

ISSN

2378-1963

e-ISSN

—

Počet stran výsledku

9

Strana od-do

241-249

Název nakladatele

IEEE

Místo vydání

Antwerp, Belgium

Místo konání akce

Antwerp, Belgium

Datum konání akce

1. 1. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000621582600026