data-engineer video for a financial analytics firm analyzes historical trading data using an Amazon Redshift cluster. To improve query performance without
A financial analytics firm analyzes historical trading data using an Amazon Redshift cluster. To improve query performance without additional costs, the data engineer seeks to optimize data distribution across cluster nodes. The dataset consists of large transaction tables exceeding 500 GB and numerous smaller dimension tables under 5 MB. What strategy should the data engineer employ to enhance query efficiency in Redshift given the varying table sizes, without expanding the cluster?