During data cleansing, an analyst conducts measures of central tendency on a data set. Which of the following data is the analyst attempting to identify?

Duplicate data is typically identified using unique identifiers or direct comparison, not primarily through measures of central tendency.

Missing data is usually identified by checking for null values or gaps, not by calculating central tendency measures.

Measures of central tendency (mean, median, mode) can be significantly affected by outliers, which are data points that deviate significantly from other observations. By analyzing these measures, an analyst can detect unusual or extreme values that might indicate data errors or anomalies requiring cleansing.

Invalid data refers to data that does not conform to defined rules or formats, which is checked by validation rules rather than central tendency measures.