A company runs an AWS Glue ETL job every day at the same time to process XML data stored in an Amazon S3 bucket. New data is added to the S3 bucket daily. A solutions architect notices that AWS Glue is reprocessing all the data each run. What should the solutions architect do to prevent AWS Glue from reprocessing old data?

Using job bookmarks is the correct solution because they track previously processed data, allowing AWS Glue to process only new or changed data in subsequent runs. This prevents reprocessing of old data, saving time and resources. Deleting data after processing is not a viable solution as it would remove the source data, which might be needed for other purposes or future analysis. Setting NumberOfWorkers to 1 would reduce parallelism and slow down the job without addressing the reprocessing issue. A FindMatches ML transform is used for finding duplicate records within a dataset, which is unrelated to preventing reprocessing of already processed data.