A recent development in data valuation introduces a geometric approach based on statistical leverage scores, offering a promising alternative to the traditional Shapley value method. The conventional Shapley approach, while effective, is known for its high computational intensity, which limits scalability in large datasets. In contrast, the new leverage score-based technique quantifies the importance of individual data points more efficiently, enhancing scalability without compromising valuation accuracy. This advancement aims to improve dataset curation and pricing by providing a more practical and scalable tool for assessing data value. The method's application potential spans various domains where data quality and valuation are critical. By addressing computational challenges inherent in traditional methods, this geometric approach represents a significant step forward in data valuation practices. These insights align with ongoing research efforts documented in recent arXiv publications.