ExploringBigData

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

Part 2: https://michaelhoweely.com/2020/07/11/how-to-connect-google-data-studio-to-a-csv-file-using-bigquery-and-cloud-storage/

https://cloud.google.com/bigquery/docs/visualize-data-studio