This study aims to fill a gap in the literature by identifying, defining, and evaluating the critical success factors that impact the implementation of data intelligence in the public sector. Fourteen factors were identified, and then divided into three categories: organization, process, and technology. We used the analytical hierarchy process, a quantitative method of decision-making, to evaluate the importance of the factors presented in the study using data collected from nine experts. The results showed that technology, as a category, is the most important. The analysis also indicated that project management, information systems & data, and data quality are the most important factors among all fourteen critical success factors. We discuss the implications of the analysis for practitioners and researchers in the paper.

本研究旨在通过识别、定义和评估影响公共部门数据智能实施的关键成功因素来填补文献空白。确定了 14 个因素，然后将其分为三类：组织、流程和技术。我们使用层次分析法，一种定量的决策方法，使用从九位专家收集的数据来评估研究中提出的因素的重要性。结果表明，技术作为一个类别，是最重要的。分析还表明，项目管理、信息系统和数据以及数据质量是所有十四个关键成功因素中最重要的因素。我们在论文中讨论了分析对从业者和研究人员的影响。