You have developed a BigQuery ML linear regression model using a training dataset stored in a BigQuery table, which receives new data every minute. To automate hourly model training and direct inference, you employ Cloud Scheduler and Vertex AI Pipelines. The feature preprocessing involves quantile bucketization and MinMax scaling on data from the past hour. To minimize storage and computational overhead, what approach should you take?