In the context of designing a machine learning pipeline, assessing the quality of data is a critical step. Consider a scenario where you are tasked with developing a model to predict customer churn for a telecommunications company. The dataset includes customer demographics, service usage, and complaint history. However, preliminary analysis reveals missing values, inconsistent entries, and outliers in the complaint history. Given the importance of accurate predictions for strategic decision-making, which of the following best explains why assessing data quality is crucial in this scenario? (Choose one correct option)