Identifying duplicate records in a database is an example of which quality analysis type?

Identifying duplicate records in a database is an example of quantitative analysis because it involves measuring and assessing numerical data for accuracy and consistency. In this context, duplicates can be quantified—meaning the analysis is based on counting occurrences and evaluating the prevalence of repeated entries within the dataset.

Quantitative analysis focuses on numerical values and statistical methods to analyze data quality, such as determining how many times a specific record appears. This process is crucial in ensuring that the data is valid and reliable since duplicates can lead to incorrect conclusions if used in reporting or decision-making.

In contrast, qualitative analysis would involve subjective judgment regarding the quality of data rather than numerical measurement. Data screening generally implies a preliminary check of data for obvious errors or outliers, while data auditing encompasses a broader scope of reviewing the accuracy, completeness, and reliability of the data, which may include processes beyond just identifying duplicates.