A retail company uses Amazon Aurora PostgreSQL to process and store live transactional data. The company uses an Amazon Redshift cluster for a data warehouse.
An extract, transform, and load (ETL) job runs every morning to update the Redshift cluster with new data from the PostgreSQL database. The company has grown rapidly and needs to cost optimize the Redshift cluster.
A data engineer needs to create a solution to archive historical data. The data engineer must be able to run analytics queries that effectively combine data from live transactional data in PostgreSQL, current data in Redshift, and archived historical data. The solution must keep only the most recent 15 months of data in Amazon Redshift to reduce costs.
Which combination of steps will meet these requirements? (Choose two.)
lalitjhawar
Highly Voted 1 year, 2 months agorebasheer
Most Recent 6 days, 21 hours agoXP_2600
2 months, 1 week agoAWSMM
3 months, 4 weeks agoPalee
5 months, 1 week agoVidhi212
8 months, 2 weeks agoSambitParida
8 months, 2 weeks agorsmf
10 months agomohamedTR
10 months, 2 weeks agoHunkyBunky
1 year, 2 months agoartworkad
1 year, 2 months agotgv
1 year, 2 months agoGHill1982
1 year, 2 months ago