Optical Character Recognition is one of the most transformative technologies in the age of digitization. It has bridged the gap between human-readable content and machine learning systems by enabling machines to read and interpret text from images, PDFs, and other visual formats. For developers, researchers, and companies building OCR-powered applications, the availability of high-quality OCR Datasets plays a crucial role in achieving accurate and reliable results. It addresses OCR datasets’ relevance, their application, challenges faced, and features of an ideal dataset to learn and improve an OCR model with high precision.