A data analyst must combine service calls into low-, medium-, and high-priority levels in order to analyze organizational responses. Which of the following techniques should the analyst use for this t

Augmentation involves adding new data or transforming existing data to increase its size or diversity, not categorizing it into groups.

Imputation is the process of replacing missing data with substituted values, not for grouping existing data into categories.

Scaling is the process of transforming data to fit within a specific range or distribution, often used in machine learning, but not for creating categorical priority levels.

Binning, also known as discretization, is the process of grouping continuous or numerical data into a smaller number of 'bins' or categories. In this scenario, combining service calls into low-, medium-, and high-priority levels effectively creates distinct bins for analysis.