Content deleted Content added
No edit summary |
Tried to summarize a comparison with anchor modelling, an alternative approach, as well as how these two entity based models stands out from other approaches (entity-relational approaches?) in general.. |
||
Line 8:
The modeling method is designed to be resilient to change in the business environment where the data being stored is coming from, by explicitly separating structural information from descriptive attributes.<ref>[[#dvsuper|Super Charge your data warehouse]], page 21</ref> Data vault is designed to enable parallel loading as much as possible,<ref>[[#dvsuper|Super Charge your data warehouse]], page 76</ref> so that very large implementations can scale out without the need for major redesign.
Unlike the [[star schema]] ([[dimensional modelling]]) and the classical [[relational model]] (3NF), data vault and [[anchor modelling]] are well-suited for capturing changes that occur when a source system is changed or added, but are considered advanced techniques which require experienced [[data architect]]s.<ref>{{Kilde www|url=https://www.agero.se/blogg/ralager-istallet-for-ett-strukturerat-datalager|tittel=Rålager istället för ett strukturerat datalager|besøksdato=2023-02-22|fornavn=Johan|etternavn=Porsby|språk=sv|verk=www.agero.se}}</ref> Both data vaults and anchor models are [[Entity (computer science)|entity-based]] models,<ref>{{Kilde www|url=https://www.agero.se/blogg/datamodeller-for-data-warehouse|tittel=Datamodeller för data warehouse|besøksdato=2023-02-22|fornavn=Johan|etternavn=Porsby|språk=sv|verk=www.agero.se}}</ref> but anchor models have a more normalized approach.{{citation needed}}
== History and philosophy ==▼
▲== History and philosophy ==
{{Original research|discuss=Template talk:Original research#discuss parameter|date=August 2019}}
| |||