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A Case Study of a Data Warehouse in the Finnish Police
Abstract
The high level objectives of public authorities are to create value at minimal cost, and achieve ongoing support and commitment from its funding authority. Similar to the private sector, today’s government agencies face a rapidly changing operating environment and many challenges. Where public organizations differ is that they need to manage this environment while answering to demands for increased service, reduced costs, fewer resources and at the same time increased efficiency and accountability. Public organization must cope with changing expectations of multiple contact groups, emerging regulation, changes in politics, decentralization of organization, and centralization of certain functions providing similar services, and growing demand for better accountability. The aim of public management is to create public value. Public sector managers create value through their organization’s performance and demonstrated accomplishments. The public value is difficult to define: it is something that exists within each community. It is created and affected by the citizens, businesses and organizations of that community (cf. also Moore, 1995). This increased interest to questions of value is partly due to the adoption of values and value-related concepts taken from business, like value creation and added value. It is argued that the public sector adopts business-like techniques to increase efficiency (Khademian, 1995; cf. Turban et al. 2007; Chen et al. 2005). In addition, there is a growing concern to the non-tangible, political, and ethical aspects of the public sector governance and actions (See Berg, 2001) Decision making that turns the resources in to public value is a daily challenge in the government (Khademian, 1999; Flynn, 2007) and not only because of the social or political factors. Most of decision problems are no longer well-structured problems that are easy to be solved by experience. Even problems that used to be fairly simple to define and solve are now much more complex because of the globalization of the economy, and rapid pace of changes in the technology and political and social environment. Therefore, modern decision makers often need to integrate quickly and reliably knowledge from different areas of data sources to use it in their decision making process. Moreover, the tools and applications developed for knowledge representations in key application areas are extremely diversified, therefore knowledge and data modeling and integration is important (See also the decision support systems (DSS) modeling methods and paradigms: Ruan et al., 2001; Carlsson & Fuller, 2002; Fink, 2002; Makowski & Wierzbicki, 2003). The application s of real-world problems and the abundance of different software tools allow to integrate several methods, specifications and analysis and to apply them to new, arising, complex problems.
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