You are working for a global financial company. Company locations spread across various countries upload transaction details data to the S3 bucket in the US-West region. A large amount of data is uploaded daily from each of these locations simultaneously. You are using Amazon Athena to query this data & create reports using Amazon QuickSight to create a daily dashboard for the management team. In some cases, while running queries, you are observing Amazon S3 exception errors.
Also, in the monthly bills, a high percentage of cost is associated with Amazon Athena. Which of the following could help eliminate S3 errors while querying data and reducing the cost associated with queries? (SELECT TWO)

Answer options:

A.Partition data based upon user credentials
B.Partition data based upon date & location.
C.Create a separate Workgroups based upon user groups.
D.Create a single Workgroup for all users.

Correct Answers – B and C
AWS Athena pricing is based upon per query and the amount of data scanned in each query. In the above case, each regional office is uploading a large amount of data simultaneously. This data needs to be partitioned based upon location & date. A separate Workgroup can be created based upon users, teams, applications or workloads. This will minimize the amount of data scanned for each query, improve performance & reducing cost.
Option A is incorrect as partitioning the data on user credentials is irrelevant here.
Option D is incorrect as a single Workgroup will not decrease the amount of data scanned per query. 
For more information on Partitioning data & using Workgroups, refer to the following URLs-
https://docs.aws.amazon.com/athena/latest/ug/partitions.html
https://docs.aws.amazon.com/athena/latest/ug/manage-queries-control-costs-with-workgroups.html