You are tasked with developing a fraud detection model using Keras and TensorFlow. The records of customer transactions, which serve as your dataset, are stored in a large table in BigQuery. Before training your model, you need to preprocess these records in a way that is both cost-effective and efficient. Additionally, the ultimate goal is to use the trained model for batch inference directly in BigQuery. Considering these requirements, how should you implement the preprocessing workflow?