Thesis Abstract

Abstract
In the realm of public administration, the integration of data analytics has emerged as a transformative tool to facilitate evidence-based decision-making processes. This thesis explores the potential of data analytics in enhancing decision-making within public administration contexts. The study focuses on the utilization of data analytics techniques to analyze and interpret large volumes of data, aiming to extract valuable insights that can inform strategic decision-making processes in public sector organizations. The introduction section provides a comprehensive overview of the research topic, highlighting the significance of leveraging data analytics in public administration. The background of the study delves into the evolution of data analytics and its application in the public sector, setting the context for the research inquiry. The problem statement identifies the challenges faced by public administrators in making informed decisions and emphasizes the role of data analytics in addressing these challenges. The objectives of the study are outlined to guide the research process, aiming to explore the impact of data analytics on decision-making practices in public administration. The limitations of the study are acknowledged, recognizing the constraints and potential biases that may influence the research findings. The scope of the study delineates the boundaries of the research focus, specifying the sectors and contexts within public administration that will be examined. The significance of the study underscores the potential benefits of integrating data analytics into decision-making processes, emphasizing the value of data-driven insights in enhancing organizational performance and efficiency. The structure of the thesis provides a roadmap for the organization of the research, outlining the chapters and sub-sections that will be covered in the study. The definition of terms clarifies key concepts and terminology used throughout the thesis, ensuring a common understanding of the research context. The literature review chapter synthesizes existing research and theoretical frameworks related to data analytics and decision-making in public administration. The analysis encompasses ten key themes, including data-driven decision-making, predictive analytics, performance measurement, and organizational learning. The research methodology chapter details the research design, data collection methods, sampling techniques, and data analysis procedures employed in the study. The chapter includes eight sections that outline the research approach, data sources, data collection instruments, and analytical tools used to investigate the research questions. The discussion of findings chapter presents the results of the data analysis, highlighting the key findings and insights derived from the application of data analytics techniques in public administration contexts. The chapter explores the implications of the findings for decision-making practices and organizational performance, offering recommendations for future research and practice. In conclusion, the thesis summarizes the key findings and contributions of the study, emphasizing the transformative potential of data analytics in enhancing decision-making processes in public administration. The conclusion reflects on the research objectives, discusses the implications of the study findings, and suggests avenues for further research and practice in the field of data-driven decision-making in public administration.

Thesis Overview