Anchor Modeling

Regardt, Olle; Rönnbäck, Lars; Bergholtz, Maria; Johannesson, Paul; Wohed, Petia

doi:10.1007/978-3-642-04840-1_19

Cited by 5 publications

(1 citation statement)

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“…The two prominent approaches in ensemble modeling are data vaults [16,8,4,18] and anchor modeling [23,25]. Both are actually very close [24], with a somewhat easier evolutivity and a non-destructive schema evolution for anchor modeling, but a larger number of objects to manage because of a sixth normal form (6NF) model, as well as non-automated maintenance procedures for timestamps.…”

Section: Ensemble Modeling and Data Vaultsmentioning

confidence: 99%

Modeling Data Lake Metadata with a Data Vault

Nogueira

Romdhane

Darmont

2018

Proceedings of the 22nd International Database Engineering &Amp; Applications Symposium on - IDEAS 2018

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With the rise of big data, business intelligence had to find solutions for managing even greater data volumes and variety than in data warehouses, which proved ill-adapted. Data lakes answer these needs from a storage point of view, but require managing adequate metadata to guarantee an efficient access to data. Starting from a multidimensional metadata model designed for an industrial heritage data lake presenting a lack of schema evolutivity, we propose in this paper to use ensemble modeling, and more precisely a data vault, to address this issue. To illustrate the feasibility of this approach, we instantiate our metadata conceptual model into relational and document-oriented logical and physical models, respectively. We also compare the physical models in terms of metadata storage and query response time.

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Section: Ensemble Modeling and Data Vaultsmentioning

confidence: 99%