Extended drill-down operator: Digging into the structure of performance indicators

• Published in: Concurrency and computation Vol. 28; no. 15; pp. 3948 - 3968
• Main Authors: Diamantini, Claudia, Potena, Domenico, Storti, Emanuele
• Format: Journal Article
• Language: English
• Published: Blackwell Publishing Ltd 01.10.2016
• Subjects: Algebra; Cubes; data warehouse; Design analysis; Enrichment; indicator drill-down; Indicators; Mathematical models; Obstacles; Operators; performance indicators; semantic multidimensional model
• ISSN: 1532-0626; 1532-0634
• DOI: 10.1002/cpe.3726

Summary Performance measurement is the subject of interdisciplinary research on information systems, organizational modeling and decision support systems. The data cube model is usually adopted to represent performance indicators (PI) and enable flexible analysis, visualization and reporting. However, the major obstacles against effective design and management of PI monitoring systems are related to the facts that PIs are complex objects with an aggregate/compound nature. This often leads to unawareness of indicator semantics as well as of dependencies among indicators. In this work, we propose to enrich the data cube model with the formal description of the structure of an indicator given in terms of its algebraic formula and aggregation function. Such a model enables the definition of a novel operator, namely indicator drill‐down, which relies on formula manipulation functionalities and reasoning. Like the usual drill‐down, this operator increases the detail of a measure of the data cube by expanding an indicator into its components. Thus, the two notions of drill‐down are integrated, allowing a novel way of data exploration. As a proof‐of‐concept, an implementation of the approach is presented. The evaluation of the implementation on real and synthetic scenarios enlightens the effectiveness and the efficiency of the approach. Copyright © 2015 John Wiley & Sons, Ltd.