Informace o publikaci
Developing Reliable Taxonomic Features for Data Warehouse Architectures
| Autoři | |
|---|---|
| Rok publikování | 2020 |
| Druh | Článek ve sborníku |
| Konference | Proceedings of the 22nd IEEE International Conference on Business Informatics - CBI 2020 |
| Fakulta / Pracoviště MU | |
| Citace | |
| Doi | http://dx.doi.org/10.1109/CBI49978.2020.00033 |
| Klíčová slova | data warehouse architecture; reliable feature; taxonomy |
| Popis | 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. |