OLAP Hierarchies: A Conceptual Perspective

Abstract

OLAP (On-Line Analytical Processing) tools support the decisionmaking process by giving users the possibility to dynamically analyze high volumes of historical data using operations such as roll-up and drill-down. These operations need well-defined hierarchies in order to prepare automatic calculations. However, many kinds of complex hierarchies arising in real-world situations are not addressed by current OLAP implementations. Based on an analysis of real-world applications and scientific works related to multidimensional modeling, this paper presents a conceptual classification of hierarchies and proposes graphical notations for them based on the ER model. A conceptual representation of hierarchies allows the designer to properly represent users' requirements in multidimensional modeling and offers a common vision of these hierarchies for conceptual modeling and OLAP tools implementers. * This work was funded by a scholarship of the Cooperation Department of the Université Libre de Bruxelles. ** Currently on leave from the Universidad de Costa Rica. 1 Other names, such as dimension attributes [5] or category attributes [15] are also used. 2 They also are called non-dimension attributes [5].

A survey on summarizability issues in multidimensional modeling

“…Due to this fact, several approaches [31,20,8,22] arose to define more expressive multidimensional formalisms for modeling complex real-world scenarios, whilst ensuring summarizability. The common foundation of these works is the definition of a classification of different kinds of complex multidimensional structures in order to ease the task of designers about identifying different real-world situations.…”

“…In [20,21] the authors present a classification of different kinds of complex real-world dimension hierarchies, and they define the MultiDimER model for the conceptual design of complex multidimensional models based on an extension of the well-known Entity-Relationships (ER) model. The idea is that this classification guides developers to properly capture at a conceptual level the precise semantic of different kinds of hierarchies without being limited by current data analysis tools.…”

Spatial aggregation: Data model and implementation

“…Thus, a spatial dimension is a dimension that contains at least one spatial hierarchy. This model is an extension of previous conceptual model for OLAP introduced by the same authors, based on the well-known Entity-Relationship model [29]. In the models above, spatial measures are characterized in two ways, namely: (a) measures representing a geometry, which can be aggregated along the dimensions; (b) a numerical value, using a topological or metric operator.…”

Enhancing flexibility and expressivity of contextual hierarchies

“…To this aim, data warehouses were designed to consolidate, store and organize data thanks to a multidimensional schema [1]. Often, attributes are equipped with hierarchies which allow to consider data at several levels of granularity [2]. On-Line Analytical Processing (OLAP) tools exploit these hierarchies by enabling the decision makers to aggregate and examine data at different combinations of levels [3].…”