You need to design a data retention solution for the Twitter feed data records. The solution must meet the customer sentiment analytics requirements…

Scenario: Purge Twitter feed data records that are older than two years.

Data sets have unique lifecycles. Early in the lifecycle, people access some data often. But the need

for access often drops drastically as the data ages. Some data remains idle in the cloud and is rarely

accessed once stored. Some data sets expire days or months after creation, while other data sets are

actively read and modified throughout their lifetimes. Azure Storage lifecycle management offers a

rule-based policy that you can use to transition blob data to the appropriate access tiers or to expire

data at the end of the data lifecycle.

Reference:

https://docs.microsoft.com/en-us/azure/storage/blobs/lifecycle-management-overview