DECISION SUPPORT SYSTEM IN PUBLIC ADMINISTRATION BASED ON INFORMATION AND ANALYTICAL RESOURCES
DOI:
https://doi.org/10.51547/ppp.dp.ua/2024.1.5Keywords:
public administration; state; decision-making; information support; analytical activityAbstract
In the field of public administration, the integration of advanced technological solutions has become a necessity, as traditional methods of management are giving way to more sophisticated approaches. This underscores the need for effective Decision Support Systems (DSS) as decision-making processes in government bodies evolve. The use of DSS in public administration is gaining increasing importance as the need to enhance decision-making processes in government agencies has become more prominent. The aim of this article is to analyse the decision support system of public administration based on information and analytical support. The decision support system of government bodies based on information-analytical support is analysed. A classification of DSS is proposed based on key components: systems managed by models, data, knowledge, communications, documents, and hybrid systems. Analytical tools and data processing methods necessary for effective DSS utilization are discussed, including online analytical processing, data mining, predictive analytics, simulation modelling, and optimization models, as well as text analysis and language processing. Various approaches for further improvement of information-analytical support systems are proposed, such as integration with external data sources, innovation in analytical tools, prioritizing scalable systems, establishing reliable data management systems, and creating a conducive regulatory environment for data exchange. The theoretical significance of the research lies in the systematization of decision support systems, identification of problems and constraints in modern DSS. By applying the proposed approaches and utilizing DSS capabilities, government bodies can navigate their practical activities in the technological landscape, utilize available data, and contribute to making informed decisions, ultimately enhancing adaptability, efficiency, and the ability to address complex societal challenges. While the article has a theoretical nature, the suggestions for improving DSS can be applied in the practical activities of government bodies.
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