To systematically improve any image, text, or tabular/CSV/Excel dataset, one can quickly run it through Cleanlab Studio — an automated solution to find and fix data issues using AI. The Stanford Cars dataset, originally used in a research paper with over 1000 citations, was analyzed for common issues and outliers, which were detected by Cleanlab Studio, revealing mislabeled images that affect product categorization and identification efforts in e-commerce analytics and business intelligence. These errors can have detrimental effects on modeling and analytics efforts, highlighting the importance of correcting them to produce accurate models and data-driven conclusions. Cleanlab Studio's universal Data-Centric AI platform can be used to find and fix issues in various datasets, including text, image, table/CSV/Excel, and more, offering a free solution for data improvement.