Modelling Spatial Decision Support Systems Focused on the Development of a Data Warehouse: Applying Software Engineering

Modelling Spatial Decision Support Systems Focused on the Development of a Data Warehouse: Applying Software Engineering

Concepción M. Gascueña (Higher Technical School of Computer Systems Engineering, Madrid Polytechnic, Madrid, Spain) and Rafael Guadalupe (Higher Technical School of Topography, Geodesy and Cartography, Madrid Polytechnic, Madrid, Spain)
Copyright: © 2014 |Pages: 22
DOI: 10.4018/ijdsst.2014070103
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Abstract

Nowadays, organizations have plenty of data stored in DB databases, which contain invaluable information. Decision Support Systems DSS provide the support needed to manage this information and planning medium and long-term “the modus operandi” of these organizations. Despite the growing importance of these systems, most proposals do not include its total development, mostly limiting itself on the development of isolated parts, which often have serious integration problems. Hence, methodologies that include models and processes that consider every factor are necessary. This paper will try to fill this void as it proposes an approach for developing spatial DSS driven by the development of their associated Data Warehouse DW, without forgetting its other components. To the end of framing the proposal different Engineering Software focus (The Software Engineering Process and Model Driven Architecture) are used, and coupling with the DB development methodology, (and both of them adapted to DW peculiarities). Finally, an example illustrates the proposal.
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1. Introduction

New methodologies, aimed at increasing software’s rapid development pace are sought, for through the use, of different approaches and criteria. Within Information Systems, the Decision Support Systems DSS, are systems developed with the purpose of analyzing the data stored in organizations; they are becoming increasingly important, since, due to advances in database DB technologies and the cheapening of storage resources, the organizations have more and more data stored, which is waiting to offer their valuable information. This is outstanding to such organizations, and here begins the interest in technologies such as Data Warehouse DW, also named Multidimensional MM DBs, which is an important piece in DSS; it allows for organizing, storing, recovering, and processing data in an efficient way to obtain the maximum information in the minimum time. DWs are DB that contain large amounts of data, which can come from various sources, mostly from transactional DB. According to (Inmon, 2002) a DW is “A collection of data, focused on relevant business events, integrated, non-volatile, including time as an important characteristic of reference for the decision making process”. The authors in (Abril Frade et al, 2007) define a DW as “an information system where data is collected, organized and grouped with respect to events or business activities”. In short, DWs are made to collect data and to extract the following from them: behavior analysis, trends, groupings, statistics, etc.., this information is used in DSS for the decision-making process; which will enable organizations in their planning efforts and with their long-term processes, i.e. “It studies the past to predict/plan the future”. However, there are no proposals with methodologies covering the whole development of DSS. Most proposals only focus on the development of some DW components, mainly the DW repository, losing sight of other involved components. This proposal tries of fill this void, proposing an approach to develop spatial DSS, focused on the creation of an associated spatial DW while following a Processes model. In addition, the proposal uses Software Engineering and DB methodologies as complementary focus. Both the Software Engineering Process (SEP) and the Model Driven Architect (MDA) focus within Software Engineering. Moreover, within DB Methodologies, MM data models regarded as MDA models, are used. Next, it explains some concepts used in this paper to facilitate its understanding.

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