Analysed SEVIR and Storm Datasets and visualized the data using Big Query on Data Studio. Datasets: Sevir Data: The Storm EVent ImagRy (SEVIR) dataset is a collection of temporally and spatially aligned images containing weather events captured by satellite and radar. Each of these "events" consists of 4 hours of data in 5 minute time increments over a 384 km x 384 km patch sampled somewhere over the US. Each event is SEVIR is captured by up to 5 image types. https://nbviewer.org/github/MIT-AI-Accelerator/eie-sevir/blob/master/examples/SEVIR_Tutorial.ipynb
Storm Data: Contains information about events occurred between 1950 and 2021 as entered by NOAA's National Weather Service (NWS).
Ref: https://www.ncdc.noaa.gov/stormevents/ftp.jsp
Part 1: Implementing Jupyter Notebook
Part 2 : BigQuery and Data Studio
References: Part 1: https://github.com/MIT-AI-Accelerator/sevir_challenges
https://nbviewer.org/github/MIT-AI-Accelerator/eie-sevir/blob/master/examples/SEVIR_Tutorial.ipynb
https://cloud.google.com/bigquery/docs/visualize-data-studio
