The data quantity and quality balance is context-dependent and should be evaluated iteratively. While having a large amount of data can help train more complex models, poor-quality data can lead to poor performance. It's crucial to start with high-quality data and assess whether the quantity is sufficient based on the model's performance. If the model's performance is lacking, consider strategies for acquiring more high-quality data.