Uncovering Data Quality Issues in Big Healthcare Data: Implications for Accurate Analytics

Data quality assessment is a critical aspect of analyzing big healthcare data to ensure accurate analytics. This paper emphasizes the crucial role of data quality assessment in the analysis of big healthcare data to ensure accurate analytics. It explores the importance of data quality assessment and its implications for reliable healthcare analytics. The paper discusses various data quality issues that can impact healthcare datasets and emphasizes the need to address them effectively. Methods for data quality assessment are presented, enabling the identification and resolution of data quality issues. Additionally, the paper highlights the use of standardized data quality indicators to evaluate the reliability of healthcare data. We propose an Integrated model for Assessing Data Quality in Healthcare. In conclusion, this research underscores the significance of data quality assessment for trustworthy analytics and informed decision-making in the healthcare domain.