A Novel Query-Based Approach for Addressing Summarizability Issues in XOLAP
Marouane Hachicha (ERIC), Chantola Kit (ERIC), J\'er\^ome Darmont, (ERIC)

TL;DR
This paper introduces a new query-based method for automatically detecting and resolving summarizability issues in XML-based multidimensional data models, improving accuracy and scalability in complex hierarchical data analysis.
Contribution
It presents a novel query-time approach that handles summarizability problems in XML MD models without altering data or models, unlike previous methods.
Findings
Effective detection and processing of summarizability issues at query time.
Focus on XML models better suited for complex hierarchies.
Scales better than existing reference approaches.
Abstract
The business intelligence and decision-support systems used in many application domains casually rely on data warehouses, which are decision-oriented data repositories modeled as multidimensional (MD) structures. MD structures help navigate data through hierarchical levels of detail. In many real-world situations, hierarchies in MD models are complex, which causes data aggregation issues, collectively known as the summarizability problem. This problem leads to incorrect analyses and critically affects decision making. To enforce summarizability, existing approaches alter either MD models or data, and must be applied a priori, on a case-by-case basis, by an expert. To alter neither models nor data, a few query-time approaches have been proposed recently, but they only detect summarizability issues without solving them. Thus, we propose in this paper a novel approach that automatically…
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Taxonomy
TopicsAdvanced Database Systems and Queries · Semantic Web and Ontologies · Data Quality and Management
