What is the purpose of data completeness analysis in data quality assessment?
- To identify missing data values
- To improve data accuracy
- To optimize data storage
- To remove duplicate records
The purpose of data completeness analysis in data quality assessment is to identify missing data values within a dataset. It involves examining each attribute or field to determine if any essential information is absent. By identifying missing data, organizations can take corrective actions such as data collection, imputation, or adjustment to ensure that the dataset is comprehensive and suitable for analysis. Ensuring data completeness is crucial for maintaining the integrity and reliability of analytical results and business decisions.
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