Exam AWS Certified Data Analytics - Specialty topic 1 question 64 discussion

Option A as the COPY command loads data in parallel from Amazon S3, Amazon EMR, Amazon DynamoDB, or multiple data sources on remote hosts. COPY loads large amounts of data much more efficiently than using INSERT statements, and stores the data more effectively as well. Amazon S3 provides eventual consistency for some operations. Thus, it's possible that new data won't be available immediately after the upload, which can result in an incomplete data load or loading stale data. You can manage data consistency by using a manifest file to load data Option C as you can efficiently update and insert new data by loading your data into a staging table first. Amazon Redshift doesn't support a single merge statement (update or insert, also known as an upsert) to insert and update data from a single data source. However, you can effectively perform a merge operation. To do so, load your data into a staging table and then join the staging table with your target table for an UPDATE statement and an INSERT statement.

Point 5 is also important to note in the article mentioned by Subho_in. Also look at this why to use Staging tables: https://docs.aws.amazon.com/redshift/latest/dg/merge-create-staging-table.html

"The organization want to load the dataset onto Amazon Redshift". answer E is not moving any data not does help with it