Knowledge Discovery In Government Decision Making Process "a Study Of Swedish Government Agencies And Publicly Owned Companies"  

Abstract Category: Science
Course / Degree: Master
Institution / University: Lund, Sweden
Published in: 2009

Dissertation Abstract / Summary:

The computerization of government transactions results in dramatic increase in growth of data across government agencies. This data is presented, generated, maintained and used independently in each government department and agencies which leads to poor decisions and isolated planning. This environment hinders effective access to data, reuse and aggregation, so that decision makers can get useful information at the right time and in the right format, which can guide them in decision making process. Given the turbulent environment and complex decision situations that the government decision is characterized, there is need to extract useful knowledge from these data to enable decision makers to access useful and sufficient knowledge. Therefore, there is need for effective techniques and tools to integrate the data from different sources into a consistent format, which permit the decision maker to access a cleansed and consistent data, and also derives useful knowledge.

Knowledge discovery in databases (KDD) is such techniques that extracts and identifies useful Knowledge from huge data sets; hence assist decision makers in the process of effective decision making. This study explore the perceived usefulness of the knowledge discovered through the knowledge discovery in database (KDD) in the decision making process of government agencies. The empirical findings collected from Sweden Government Agencies have attempted to explore the perceived usefulness of knowledge on the decision making process therefore add to the understanding of knowledge discovery and use of such knowledge by decision makers in the government.

Dissertation Keywords/Search Tags:
decision making, data warehouse, KDD, Data Mining, eGovernment, Perceived Usefulness, systemteori

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Submission Details: Dissertation Abstract submitted by Imad Banihani from Jordan on 02-Jan-2012 21:59.
Abstract has been viewed 2723 times (since 7 Mar 2010).

Imad Banihani Contact Details: Email: imad.banihani@gmail.com

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