Because correctness matters, how do many experienced professionals feel about relying on fully automated tools for database redesign without careful oversight?

Introduction / Context:
Schema changes can break applications, violate data quality, and degrade performance. While automation accelerates repetitive tasks, it cannot replace human judgment about business rules, edge cases, and migration nuances. This question asks about the prevailing professional attitude toward fully automated redesign.

Given Data / Assumptions:

• Automated tools can generate DDL and migration scripts.
• Real databases have legacy quirks and undocumented constraints.
• Data migration requires validation and reconciliation steps.

Concept / Approach:

Many practitioners adopt a cautious stance. They use automation for scaffolding and repeatable operations but verify, test, and often customize the output. Hence, “skeptical” best describes their view of depending solely on automation without human oversight and rigorous testing.

Step-by-Step Solution:

Verification / Alternative check:

Post-deployment audits and benchmarks often reveal issues that automation missed (for example, missing indexes for new access paths or unintended constraint interactions).

Why Other Options Are Wrong:

Optimistic/Ambivalent: do not reflect the prudent caution necessary for high-impact schema changes.

None of the above: incorrect because “skeptical” is appropriate.

Common Pitfalls:

Trusting default tool assumptions, skipping data validation after automated migrations, and failing to capture domain-specific rules that tools cannot infer.

Final Answer:

skeptical