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A company is developing a solution to manage inventory data for a group of automotive repair shops. The solution will use Azure Synapse Analytics as the data store.
Shops will upload data every 10 days.
Data corruption checks must run each time data is uploaded. If corruption is detected, the corrupted data must be removed.
You need to ensure that upload processes and data corruption checks do not impact reporting and analytics processes that use the data warehouse.
Proposed solution: Create a user-defined restore point before data is uploaded. Delete the restore point after data corruption checks complete.
Does the solution meet the goal?
A . Yes
B . No
Answer: A
Explanation:
User-Defined Restore Points
This feature enables you to manually trigger snapshots to create restore points of your data warehouse before and after large modifications. This capability ensures that restore points are logically consistent, which provides additional data protection in case of any workload interruptions or user errors for quick recovery time.
Note: A data warehouse restore is a new data warehouse that is created from a restore point of an existing or deleted data warehouse. Restoring your data warehouse is an essential part of any business continuity and disaster recovery strategy because it re-creates your data after accidental corruption or deletion.
Reference: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/backup-and-restore
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