Dashboard Week. Day 2

by Amalia García-Vellido Santías

For day 2 of Dashboard Week our has been to analyse data about Hail Storms in America.

The data can be found here: https://www.spc.noaa.gov/gis/svrgis/  (National Oceanic and Atmospheric Administration -  NOAA) and one of the requirements for the final dashboard was that we needed to create it using the Alteryx Reporting Tools which we had not used previously, so it was the main challenge of the day.

My thinking process and steps for today:

  • Input data and explore, read documentation about the meaning of each field. What fields do I want to include in my analysis? Do I need to rename or change data types?
  • Think about questions that can be answered  and start my analysis

1.  What is the total number of hail storm by year? which year in the dataset has the maximum # of hail storms.

I used a summarize to transform the data in the values I needed in order to create a line chart

2.  Is there a particular season that has the biggest number of storms? to answer this, I used 3 formula tool to create the fields needed, such as season, percent of total.

with this flow my aim was to have the number to build a pie chart:

3. The date field in the dataset had also the hour of the storm, so why not try to find if there is a time frame that accounts for the highest number of storms?  Wow! more than half of the storms in the dataset happened  between 16:00 and 19:00

4. Analysis by state, with the summarize I calculated total the number of hail storms by state, then I joined with a shape file containing USA states, and created a filled map

Until this point, I have been analyzing the total number of hail storms by different factors, time, year, location.

The last piece of analysis involves the movement of the tornado, since in the data I had start latitude and longitude and end latitude and longitude I created two points for the start and end of and got the distance between then.

I created a map for the maximum distance by a tornado for each state, and the maximum in the whole dataset.

Using the layout, header, and footer tools, you create a report/dasbhoard than can be outputted as a PDF.

I am happy to have completed by now 40% of the dashboard week :)


Amalia García-Vellido Santías

Fri 26 Mar 2021

Thu 25 Mar 2021