The annual IEEE Big Data conference is a top tier research conference in Big Data. The conference provides a leading forum for publicizing the latest results in Big Data Research, Development, and Applications. Every year it solicits high-quality original research papers in any aspect of Big Data with an emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) This year IFT co-authored and presented the paper “Comparative Study of 3D Point Cloud Compression Methods” at the 2021 IEEE International Conference on Big Data (IEEE BigData 2021). The paper discusses a comprehensive study of various approaches in point cloud compression (PCC). The results assist in creating an adaptive 3D point cloud stream compression benchmark that is efficient and beneficial from different PCC techniques. The authors of this paper include Mai Bui, Lin-Ching Chang, Hang Liu, Qi Zhao, and Genshe Chen.