You are working on a machine learning project where you need to train a TensorFlow model on a structured dataset containing 100 billion records, stored across multiple CSV files. The project is constrained by tight deadlines and a limited budget, requiring an efficient solution that minimizes costs while maximizing performance. Additionally, the solution must be scalable to accommodate future data growth. Given these constraints, which of the following approaches would BEST improve the input/output execution performance for training your TensorFlow model? Choose the two most effective options.