Fine-tuning large language models (LLMs) has emerged as a crucial technique to adapt these models for specific domains. Traditionally, fine-tuning relied on massive datasets. However, Data-Centric Fine-Tuning (DCFT) presents a novel methodology that shifts the focus from simply expanding dataset size to optimizing data quality and appropriateness f