The correct answer is A. Data Sampling.
Data sampling is the process of selecting a subset of data from a larger dataset for analysis. The goal of data sampling is to reduce the size of the dataset while still maintaining a representative sample of the original data. This can be done in a number of ways, such as simple random sampling, stratified sampling, or cluster sampling.
Data integration is the process of combining data from multiple sources into a single dataset. This can be done in a number of ways, such as using a data warehouse or a data lake. The goal of data integration is to create a single, unified view of the data that can be used for analysis.
Data transformation is the process of converting data from one format to another. This can be done in a number of ways, such as using a data transformation tool or a programming language. The goal of data transformation is to make the data more compatible with the analysis tools that will be used.
Data cleaning is the process of identifying and correcting errors in data. This can be done in a number of ways, such as using a data cleaning tool or a programming language. The goal of data cleaning is to ensure that the data is accurate and reliable before it is used for analysis.