What is the difference between data profiling and data monitoring in the context of data quality assessment?
- Data profiling analyzes the structure and content of data at a static point in time, while data monitoring continuously observes data quality over time.
- Data profiling assesses data accuracy, while data monitoring assesses data completeness.
- Data profiling focuses on identifying outliers, while data monitoring identifies data trends.
- Data profiling involves data cleansing, while data monitoring involves data validation.
Data profiling involves analyzing the structure, content, and quality of data to understand its characteristics at a specific point in time. It helps identify data anomalies, patterns, and inconsistencies, which are essential for understanding data quality issues. On the other hand, data monitoring involves continuously observing data quality over time to detect deviations from expected patterns or thresholds. It ensures that data remains accurate, consistent, and reliable over time, allowing organizations to proactively address data quality issues as they arise.
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