Exploring Braj Bhasha for Text Analytics, A Comprehensive Preprocessing Approach

India's linguistic landscape is incredibly diverse, characterized by numerous languages and dialects, often with significant variations. This research addresses the challenges of Natural Language Processing (NLP) in low-resource languages by focusing on data pre-processing techniques for Braj Bhasha. This study significantly contributes to Braj Bhasha by creating a new dataset due to the limited resources available for the language. There were a total 17, 356 words present in the dataset, a curated stop word list with 44 words is created and utilized on the dataset, improving its applicability for further NLP operations. The pre-processed dataset is a significant resource with reduction in 7.5% words that enables and facilitates further study and development of NLP applications for Braj Bhasha. This initiative seeks to address the technological gap and enhance the representation of under-resourced languages in the expanding domain of natural language processing.