PDE - Storing Data - Section 3.3

Manage data lakes by configuring discovery, access controls, cost controls, data processing, and monitoring.

Configure a Cloud Storage-backed data lake using Dataplex for automated data discovery, access control policies, and quality monitoring, and apply cost controls such as lifecycle rules and storage classes to balance availability against expenditure.

Cloud StorageDataplexData lakeAccess control

Practice question for this objective

Free sampleStoring Datamedium

A genomics startup uses a Cloud Storage bucket as the landing zone of its data lake. Files arrive continuously and are read heavily for the first 30 days, occasionally between 30 and 180 days, and almost never after 180 days, but compliance requires the team to keep every object for at least seven years. The finance team wants to minimise storage cost without changing the application that writes and reads objects by their existing paths. Which configuration best meets these goals?

  • AManually copy objects older than 30 days into a separate Coldline bucket and update the application to read from both buckets depending on object age.
  • BEnable Autoclass on the bucket and additionally set a lifecycle rule that deletes objects after 180 days to control cost.
  • CConfigure an object lifecycle policy on the bucket that transitions objects to Nearline storage after 30 days and to Archive storage after 180 days, while leaving the bucket location and object names unchanged. Correct
  • DRecreate the bucket as Archive storage class from day one and rely on early-deletion fees being waived for compliance use cases to control short-term costs.
Apply Cloud Storage lifecycle rules to move data through storage classes that match its access pattern while preserving retention requirements. Cloud Storage lifecycle management evaluates configured conditions such as object age and transitions objects to colder storage classes in place, which preserves bucket name, object paths, and application behaviour. Combining a Nearline transition for cool data and an Archive transition for cold data aligns cost with access frequency while leaving the seven-year retention intact.

Why A is wrong: Manual copies double-handle data and force application changes to look up the right bucket, which is operationally fragile and does not exploit Archive pricing for the long tail of seven-year retention.

Why B is wrong: Autoclass would manage class transitions, but the additional deletion rule directly violates the seven-year retention requirement, so this configuration is not safe even though it appears cost optimal.

Why C is correct: Lifecycle rules transition objects between storage classes in place, so existing paths and the application remain unchanged while older objects move to cheaper Nearline and Archive classes that match their access frequency.

Why D is wrong: Archive class incurs higher retrieval and minimum-storage-duration charges for objects accessed in the first 30 days, and there is no general waiver of early-deletion fees, so heavily read recent objects would become expensive.

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