The correct answer is C. Data imputation.
Data imputation is the process of filling in missing values in a dataset. This can be done using a variety of methods, such as mean imputation, median imputation, or regression imputation. The goal of data imputation is to create a complete dataset that can be used for analysis.
Data visualization is the process of representing data in a graphical or pictorial format. This can be done using a variety of tools, such as charts, graphs, and maps. The goal of data visualization is to make data easier to understand and interpret.
Data aggregation is the process of combining data from multiple sources into a single dataset. This can be done using a variety of methods, such as merging, joining, and pivoting. The goal of data aggregation is to create a dataset that is more manageable and easier to analyze.
Data normalization is the process of transforming data so that it has a standard distribution. This can be done using a variety of methods, such as standardization, z-score transformation, and min-max normalization. The goal of data normalization is to make data easier to compare and analyze.