To ensure data stream quality root cause analysis and remediation, methods such as data profiling, data quality monitoring, and data quality scorecards can be used. Data profiling is used to identify patterns in the data that may indicate a problem, while data quality monitoring is used to detect and alert on data quality issues. Data quality scorecards are used to track the performance of data quality metrics over time. Additionally, data cleansing and data transformation techniques can be used to improve the quality of the data.