A company tags each financial transaction record as either personal or business and stores that category with the record. Which data-preparation step does this describe?

Data labeling is the process of identifying raw data (images, text files, videos, etc.) and adding one or more meaningful and informative labels to provide context. In this scenario, assigning "personal" or "business" to each financial transaction record is a form of data labeling, which is crucial for supervised machine learning tasks where the model learns from labeled examples. Data encoding involves converting data into a specific format, often numerical, for processing. Data normalization scales numerical data to a standard range, preventing features with larger values from dominating the learning process. Data balancing techniques address imbalanced datasets where one class has significantly more samples than others, which is not the primary activity described here.