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In the context of developing a machine learning model for a financial services company, maintaining data consistency is paramount. The company aims to predict customer churn with high accuracy. The dataset includes customer transactions, demographics, and service usage patterns. However, the data comes from multiple sources with varying formats and standards. Which of the following best explains why ensuring data consistency is crucial in this scenario? (Choose one correct option)
A
To ensure the model's predictions are based on accurate and uniform data, thereby reducing the risk of biased outcomes.
B
To simplify the model architecture, making it easier to implement and maintain.
C
To minimize the computational resources required for training the model.
D
To guarantee that the model can process data in real-time without any delays.