feat: add validation layers for generated datasets

[bella-247]

This pull request introduces a comprehensive validation framework for generated datasets, ensuring that all schema constraints are enforced after data generation. The new validator package checks for NOT NULL, PRIMARY KEY, UNIQUE, and FOREIGN KEY violations, and aggregates all errors into a structured validation result. The main changes are grouped as follows:

Core validation logic and architecture:

• Added the validator package, including the main Validate function, which checks all schema constraints for a generated dataset and returns a ValidationResult listing every violation. This includes helper types and functions for error reporting and primary key indexing.

Constraint-specific validation checks:

• Implemented checkNotNull to ensure all NOT NULL columns have non-nil values in every row.
• Implemented checkPrimaryKey to verify that primary key columns are non-nil and that primary key values are unique across all rows.
• Implemented checkUnique to enforce uniqueness constraints on specified column sets, reporting any duplicate value combinations.
• Implemented checkForeignKeys to ensure that all foreign key values reference existing primary key values in the referenced table, handling both single-column and composite keys.## What does this PR do?

Why is it needed?

Closes #

How was it tested?

Does it change any existing behavior?

Checklist

• Tests added or updated
• make test passes (go test ./... -race)
• make lint passes (golangci-lint run ./...)
• No cross-stage imports (parser doesn't import generator, etc.)
• No time.Now() or unseeded randomness in the generation pipeline
• Error messages follow the format in SRS §12.2
• Exported functions have doc comments
• Golden files updated if output format changed (make test-golden UPDATE=true)

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