In machine learning, " Data Typing " is foundational. If a numerical field (like Grade Percent) is stored as an " Object " (string/text), the AI model cannot perform mathematical operations on it, such as calculating correlations or averages. According to the AAIA™ manual, this is a " Data Quality " failure that leads to " Feature Exclusion, " where the model simply ignores the variable or treats each number as a unique text label, losing all quantitative meaning. The other formats (Integer, Float, Boolean) are appropriate for their respective data types.