The current trends in biomedical research especially genome sequence analysis are enriched by the introduction of the high-throughput sequencing technique. High-throughput sequencing like next generation sequencing (NGS) plays a crucial role in the area of whole genome sequencing (WSG), epigenomics, transcriptomics, and many more. NGS data give a deeper insight into the results of various microbial and cancer genomics analysis. NGS data are focusing on quality and diversity over the traditional biological datasets. NGS data make the process of classification, clustering, and analysis more reliable with the help of advanced computational intelligence techniques like machine learning (ML) and deep learning (DL). The accuracy of the result mostly depends upon the dataset standard, similarly, the analysis of data is more effective when it is in normalized form. In this paper, we prepare a pipeline for preprocessing of NGS data of oral cancer and breast cancer into a normalized form and make them analysis-ready. The obtained result is in a standard format with normalized values. The normalized values of NGS dataset provide an ultra-edge dimension to the analysis process and help to obtain more accurate results.