The correct answer is A. Data Deduplication.
Data deduplication is the process of identifying and removing duplicate records from a dataset. This can be done by comparing the values of each record to the values of all other records in the dataset. If two records have the same values for all of their fields, they are considered duplicates and can be removed.
Data deduplication can be used to improve the performance of data analysis and machine learning tasks. By removing duplicate records, these tasks can be performed more quickly and efficiently. Additionally, data deduplication can help to reduce the size of a dataset, which can save storage space and improve the performance of data storage and retrieval systems.
Data aggregation is the process of combining multiple data points into a single data point. This can be done by calculating the sum, average, or other statistic of the data points. Data aggregation can be used to summarize data, identify trends, and make predictions.
Data scaling is the process of adjusting the values of data points so that they fall within a specific range. This can be done by multiplying or dividing the values by a constant. Data scaling can be used to improve the performance of data analysis and machine learning tasks. By scaling the data, these tasks can be performed more accurately and efficiently.
Data encoding is the process of converting data from one format to another. This can be done by converting text to numbers, numbers to text, or one type of number to another type of number. Data encoding can be used to improve the performance of data storage and retrieval systems. By encoding the data, it can be stored more compactly and retrieved more quickly.