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Data Warehouse Fixer: Fixing Inconsistencies in Data Warehouses

Authors: Mónica Caniupán Marileo; Alvaro Placencia;

Data Warehouse Fixer: Fixing Inconsistencies in Data Warehouses

Abstract

Dimensions in Data Warehouses (DWs) are set of elements connected by a hierarchical relationship. Usually, dimensions are required to be strict and covering to support summarizations at different levels of granularity. A dimension is strict if all they rollup relations are functions, and is covering if every element in a category is connected with an element in its ancestor categories. We present the Data Warehouse Fixer (DWF), a system that restores consistency of dimensions that fail to satisfy their strictness constraints. The system checks consistency, computes minimal repairs for inconsistent dimensions by implementing Datalog programs with negation and weak constraints, and also fixes inconsistent dimensions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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