The Earth Science Data Analytics (ESDA) Cluster has made great strides in understanding the utilization of data analytics in Earth science, an area virtually untouched in the literature. In achieving its goal to support advancing science research that increasingly includes very large volumes of heterogeneous data, the ESDA Cluster is in the process of categorizing existing tools and techniques utilized in Earth science data analytics data preparation, reduction, and analysis. This session will provide a student's 'student of Data Science' point of view showcasing the usage and usability of Data Analytics. This will set the stage to address a more detailed ESDA categorization, and begin the discussion on how best to perform the gap analysis between data analytics research needs and tools/techniques available.