Data anomalies such as duplicates, null values, or outliers can be identified in database testing using a variety of methods, including:
Data Profiling:Data profiling is the process of collecting and analyzing data to understand its characteristics. This can be done using a variety of tools, such as database discovery tools, data quality tools, and data mining tools. Data profiling can be used to identify data anomalies by looking for data that is out of range, inconsistent, or missing.
Data Analysis: Data analysis involves examining, purifying, modifying, and shaping data to uncover valuable insights, inform conclusions, and aid in decision-making.Data analysis can be used to identify data anomalies by looking for data that does not fit the expected patterns.
Data Visualization:Data visualization is the process of transforming data into a visual format that can be easily understood. Data visualization can be used to identify data anomalies by looking for data that stands out from the rest.