A company is planning on using DynamoDB as a data store for their application. Below are the data access patterns for the table
Data is uploaded to the table via an application
The data is heavily used within a week’s time from the ingestion of data
After a week’s time, the data is not frequently used
Which of the following can be used to effectively store the table data in DynamoDB? Choose 2 answers from the options given below

Answer options:

A.Create tables based on a weekly basis. Ensure a high read and write capacity for these tables.
B.Change the Read and write capacity to a lower value after a week’s time for the table
C.Create a table and ensure a datetimestamp is placed as the partition Key
D.Perform scan operations on the table and delete table data which has an older datetimestamp of more than one week

Answer – A and B
An example of this is given in the AWS Documentation
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Design Pattern for Time-Series Data
Consider a typical time-series scenario, where you want to track a high volume of events. Your write access pattern is that all the events being recorded have today`s date. Your read access pattern might be to read today`s events most frequently, yesterday`s events much less frequently, and then older events very little at all.
The read access pattern is best handled by building the current date and time into the primary key. But that is certain to create one or more hot partitions. The latest one is always the only partition that is being written to. All other partitions, including all the partitions from previous days, divert provisioned write capacity from where you need it most.
The following design pattern often handles this kind of scenario effectively:
Create one table per time period, provisioned with write capacity less than 1,000 write capacity units (WCUs) per partition-key value, and minimum necessary read capacity.
Before the end of each time period, prebuild the table for the next period. Just as the current period ends, direct event traffic to the new table. You can assign names to these tables that specify the time periods that they have recorded.
As soon as a table is no longer being written to, reduce its provisioned write capacity to 1 WCU and provision whatever read capacity is appropriate. Reduce the provisioned read capacity of earlier tables as they age, and archive or delete the ones whose contents will rarely or never be needed.
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Options C and D even though possible are less efficient since we are using the scan operation to delete the data in the tables
For more information on time series data for DynamoDB, please refer to the below URL
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-time-series.html