Because database redesign requires deep SQL knowledge and careful schema refactoring, many teams rely on automated tools and generators to assist the redesign process. Is this generally a fair characterization?

Introduction / Context:
Database redesign encompasses reverse engineering, normalization, refactoring, migration planning, and impact analysis on applications and reports. Due to complexity and risk, teams often use specialized tooling to automate portions of the workflow.

Given Data / Assumptions:

• Redesign affects DDL, constraints, indexes, and stored code.
• Downstream dependencies include ETL, APIs, ORMs, and BI models.
• Tools can automate discovery, dependency mapping, and script generation.

Concept / Approach:
Automation assists but does not replace engineering judgment. Tools build dependency graphs, suggest keys and FKs, compare schemas, and generate change scripts. They also help validate data quality, enforce naming standards, and produce migration plans with rollback steps.

Step-by-Step Solution:
Reverse engineer the current schema and dependencies.Identify normalization or partitioning opportunities.Use tooling to generate DDL diffs and migration scripts.Dry-run migrations in non-production; benchmark key queries.Deploy with monitoring and backout plans.

Verification / Alternative check:
Compare manual and tool-generated plans for coverage and accuracy; unit and integration tests confirm behavior.

Why Other Options Are Wrong:
The statement is not limited to NoSQL or empty databases; automation benefits most environments.

Common Pitfalls:
Overreliance on tools without understanding semantics; inadequate testing of generated scripts.

Final Answer:
Correct