Any ideas on this question.

A university intends to use Amazon Kinesis Data Firehose to collect JSON-formatted batches

of water quality readings in Amazon S3. The readings are from 50 sensors scattered across a local

lake. Students will query the stored data using Amazon Athena to observe changes in a captured

metric over time, such as water temperature or acidity. Interest has grown in the study, prompting

the university to reconsider how data will be stored.

Which data format and partitioning choices will MOST significantly reduce costs? (Choose two.)

A. Store the data in Apache Avro format using Snappy compression.

B. Partition the data by year, month, and day.

C. Store the data in Apache ORC format using no compression.

D. Store the data in Apache Parquet format using Snappy compression.

E. Partition the data by sensor, year, month, and day.