Data Quality and Data Governance: Investigating the Impact on Data Science Outcomes

Abstract: The purpose of this study is to evaluate the effects that high data quality and effective data governance have on the outcomes of data science, with a particular emphasis on the vital roles that these factors play in improving decision-making within businesses. The rising use of data science projects by enterprises for the purpose of digital transformation presents major hurdles, particularly with regard to the trustworthiness of data and compliance with appropriate legal frameworks. A high data quality improves model accuracy, decision-making efficiency, and error reduction, while good governance boosts compliance with rules, data security, and accessibility, according to the findings of the study, which were derived from an analysis of data collected from professionals working in data science and related sectors. These findings demonstrate the synergy that exists between data quality and governance, underscoring the fact that businesses may obtain more dependable and trustworthy outcomes by prioritizing these components, which in turn supports digital transformation programs that are effective and responsible.