The correct answer is D. Data Aggregation.
Data preprocessing is the process of cleaning, transforming, and organizing data so that it can be used for analysis. Data aggregation is the process of combining data from multiple sources into a single dataset. This is not a common data preprocessing technique because it is typically done after the data has been cleaned and transformed.
Data encoding is the process of converting data into a format that can be used by a computer. This is a common data preprocessing technique because it is necessary to convert data into a format that can be stored and processed by a computer.
Data normalization is the process of rescaling data so that it has a common range. This is a common data preprocessing technique because it can help to improve the accuracy of statistical analysis.
Data imputation is the process of filling in missing values in a dataset. This is a common data preprocessing technique because it can help to improve the accuracy of statistical analysis.