A financial services company is developing a machine learning model to predict fraudulent transactions. The model requires efficient storage and retrieval of transaction data for both training and real-time inference. The dataset includes transaction IDs, timestamps, amounts, and other relevant features. The company plans to use Amazon DynamoDB for its scalability and low-latency performance. Which design pattern should the company use to structure the data in DynamoDB to meet these requirements?