Abstract
Information systems and in particular data warehouses are very expensive systems to develop. It is therefore not advisable to experiment with ideas too different from current practices. This makes it difficult to apply prescriptive theories in an existing field. From theoretical considerations one might want to develop a data warehouse according to another method such as critical systems thinking methodology. It is however very difficult to persuade data warehouse practitioners to attempt such an experiment. This might be because they would rather adhere to known practices or that they are not sufficiently knowledgeable on critical systems thinking (or any other prescriptive theory) to apply it to such an expensive project. This paper describes a method in which prescriptive theories may be used descriptively to analyse their applicability in a specific field of application. The proposed method is used to understand the practices of the data warehouse discipline from the perspectives of the systems thinking discipline. It is also indicated how this method could be used in other studies where the behaviour of participants is viewed from a point of view of which the detail are unknown to the participants.Keywords: Data warehousing, Systems thinking, Prescriptive theory, Descriptive theory, Interpretative research. Disciplines: Information technology, systems theory, data warehousing, hermeneutics
Highlights
Introduction to Data WarehousingInmon (1996) defines a data warehouse as a “subject oriented integrated, non-volatile, and time variant collection of data in support of management decisions.” Kimball et al (1998) defines a data warehouse as “the queryable source of data in the enterprise.” Sen and Sinha (2005) performed an extensive investigation into the use of Data warehousing (DW) development methodologies
Disciplines: Information technology, systems theory, data warehousing, hermeneutics, Introduction This paper explores the nature of theory in terms of descriptive and prescriptive theories
Klein and Meyers (1999) provide more detail on this and other aspects of interpretative research in Information Systems (IS). In this case the author believes that a hard systems approach to all aspects of data warehousing may have a higher possibility of data warehouse project failure, but certain technical issues are accommodating of hard systems thinking
Summary
Inmon (1996) defines a data warehouse as a “subject oriented integrated, non-volatile, and time variant collection of data in support of management decisions.” Kimball et al (1998) defines a data warehouse as “the queryable source of data in the enterprise.” Sen and Sinha (2005) performed an extensive investigation into the use of DW development methodologies. The aim of the case studies was to determine whether the thinking leading to practices of data warehouse professionals can be linked to specific systems thinking methodologies. The aim of the case studies was to indicate that different data warehousing practitioners’ motivations are rooted in different systems thinking methodologies, their practices may seem similar. Data analysis yielded a table per case study (similar to table 3) indicating to which extent the thinking of the participants could be understood from the perspective of a specific systems thinking methodology. The completed tables in this study yielded different results in terms of thinking about data warehousing from a systems thinking perspective. The first organisation (in the banking sector) from which the analysis provided in table 3 is an excerpt had very few answers mapped in the critical systems thinking column. As two managers were interviewed they found the comparison of the allocation of their answers very interesting
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