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Data · dataset · 2026

A Taxonomy for Business Intelligence Dashboard Products

Listed in Teesside University Research Data Repository

Business Intelligence (BI) dashboards integrate heterogeneous data and analytical capabilities to support decisions.

Description

However, product-centered descriptions obscure how implementations, making it difficult to compare decision scope, data, interaction, lifecycle, and assurance. This paper addresses that comparability gap by developing an evidence-based taxonomy for BI-supported dashboard implementations.

To this end, a systematic literature review (SLR) was conducted to assemble the empirical evidence. The resulting taxonomy comprises 7 facets and 30 characteristics supported by reproducible coding questions. Its application distinguishes implementations using the same platform and reveals recurrent archetypes.

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The analysis shows that lifecycle closure and semantic assurance discriminate implementations more effectively than product prevalence, whereas predictive, prescriptive, and conversational configurations remain sparsely evidenced. The taxonomy provides researchers with a common framework for cumulative comparison and practitioners with a contingency-based procedure for defining requirements before platform selection.

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