Developing Reliable Taxonomic Features for Data Warehouse
Architectures

D 2020

Developing Reliable Taxonomic Features for Data Warehouse Architectures

YANG, Qishan, Mouzhi GE a Markus HELFERT

Základní údaje

Originální název

Developing Reliable Taxonomic Features for Data Warehouse Architectures

Autoři

YANG, Qishan (372 Irsko), Mouzhi GE (156 Čína, garant, domácí) a Markus HELFERT (276 Německo)

Vydání

Antwerp, Belgium, Proceedings of the 22nd IEEE International Conference on Business Informatics - CBI 2020, od s. 241-249, 9 s. 2020

Nakladatel

IEEE

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Kód RIV

RIV/00216224:14330/20:00115621

Organizační jednotka

Fakulta informatiky

ISBN

978-1-7281-9926-9

ISSN

DOI

http://dx.doi.org/10.1109/CBI49978.2020.00033

UT WoS

000621582600026

Klíčová slova anglicky

data warehouse architecture; reliable feature; taxonomy

Štítky

firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 14. 5. 2021 06:41, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

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.

Citovat

YANG, Qishan, Mouzhi GE a Markus HELFERT. Developing Reliable Taxonomic Features for Data Warehouse Architectures. Online. In Proceedings of the 22nd IEEE International Conference on Business Informatics - CBI 2020. Antwerp, Belgium: IEEE, 2020, s. 241-249. ISBN 978-1-7281-9926-9. Dostupné z: https://dx.doi.org/10.1109/CBI49978.2020.00033.

@inproceedings{1654178,
   author = {Yang, Qishan and Ge, Mouzhi and Helfert, Markus},
   address = {Antwerp, Belgium},
   booktitle = {Proceedings of the 22nd IEEE International Conference on Business Informatics - CBI 2020},
   doi = {http://dx.doi.org/10.1109/CBI49978.2020.00033},
   keywords = {data warehouse architecture; reliable feature; taxonomy},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Antwerp, Belgium},
   isbn = {978-1-7281-9926-9},
   pages = {241-249},
   publisher = {IEEE},
   title = {Developing Reliable Taxonomic Features for Data Warehouse Architectures},
   year = {2020}
}

TY  - JOUR
ID  - 1654178
AU  - Yang, Qishan - Ge, Mouzhi - Helfert, Markus
PY  - 2020
TI  - Developing Reliable Taxonomic Features for Data Warehouse Architectures
PB  - IEEE
CY  - Antwerp, Belgium
SN  - 9781728199269
KW  - data warehouse architecture
KW  - reliable feature
KW  - taxonomy
N2  - 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.
ER  -

YANG, Qishan, Mouzhi GE a Markus HELFERT. Developing Reliable Taxonomic Features for Data Warehouse Architectures. Online. In \textit{Proceedings of the 22nd IEEE International Conference on Business Informatics - CBI 2020}. Antwerp, Belgium: IEEE, 2020, s.~241-249. ISBN~978-1-7281-9926-9. Dostupné z: https://dx.doi.org/10.1109/CBI49978.2020.00033.

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