Which strategy is essential when migrating data to DBaaS on IBM Cloud?

Question

Options

• AChoosing a DBaaS that matches the workload's specific features and performance needs
• BMigrating all data without considering data segmentation
• CPrioritizing the migration of outdated or irrelevant data
• DIgnoring data integrity checks post-migration

• A
  85% (22)
• B
  4% (1)
• C
  4% (1)
• D
  8% (2)

Explanation

Selecting a DBaaS that aligns with your workload's specific features and performance needs (A) is the cornerstone of any successful migration - mismatched capabilities lead to degraded performance, failed queries, or costly re-migrations.

Why the distractors fail:

• B is wrong because data segmentation is critical; migrating everything blindly wastes resources and can overload the target system.
• C is backwards - you should prioritize relevant, active data, not outdated or irrelevant data which should typically be archived or discarded.
• D is dangerous; skipping post-migration integrity checks risks silent data corruption or loss going undetected in production.

Memory tip: Think "fit before flight" - you must confirm the DBaaS fits your workload before you fly your data into it. Everything else (segmentation, relevance, integrity) flows from that foundational match.

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