Evaluation of the representativeness and completeness of datasets used for training and fine-tuning AI models. Covers demographic distribution analysis, linguistic and cultural coverage, class and domain balancing, identification of representation gaps, and diversity metrics to ensure generalization and reduce systemic biases resulting from unbalanced or non-representative datasets.