Analyze Critical Success Factors in Managing Data Silos to Prevent Poor Data Quality with a Case Study Research Approach

Abstract

In the context of data silo management in the government sector, Critical Success Factors (CSFs) in data quality are becoming increasingly important, especially for government agencies. Government organizations often face specific challenges in managing data silos in a report due to the complexity of their organizational structure and the large amount of report data that needs to be managed. This research aims to identify, analyze, and understand the relationship between Critical Success Factors (CSFs) in data quality to manage data and prevent data silos in organizations or agencies in report generation using work system theory and provide recommendations for developing strategies to improve data quality in reports. Through a qualitative approach, this research will explore the strategies and practices implemented by government agencies in identifying, preventing, and addressing data silos in reports. For the research methodology, it includes internal surveys with interviews of operators in the government agency. The evaluation results are expected to provide a positive contribution to public services, in the management of report data in the digital era, provide improvements in case of anomalies and deficiencies, and provide a deep understanding related to report generation in a relevant organization or agency.