So we are in Day 2. Todays data set was interesting – UFO sightings around the world!

The first task was to scrape the data from https://nuforc.org/databan/

UFO reports can be accessed from the following four indexes:

Index by EVENT DATE
Index by STATE
Index by SHAPE OF UFO
Index by DATE POSTED

I wanted to focus on USA , hence I went with the link for STATE. It was a really good refresher on web scraping and Regex.

Data Prep

It required two steps of download to get to the final data. Make sure to cache and run the workflow .Below is a screen shot of the download. Rest of the workflow was done  using Regex  Tools.

Dashboard

For the Dashboard I used a story telling style and focused on USA. I created a trend of the sighting from 2000-2021 and compared it to the  other countries where sightings were more. Interestingly USA had far more sightings compared to the rest of the world. It seems UFO knows national boundary :).The trend seems to be decreasing in UK, however in other parts of the world there seems to be spike  during recent years.

Then I looked at the seasonality of reporting as well as the Shapes that were more often spotted.

I also read upon the UFO stories (as it is interesting for me) and the general conclusion is that as we have never been contacted by any ET and we have never found any sort of alien wreckage so far .So it is safe to assume that these sightings are human fascination or anomalies in the sky. However, it is not crazy to keep an eye on it . We never know who is watching us!!!!

 

 

 

Asha Surabhi
Author: Asha Surabhi

Asha is a Computer Science graduate with 8+ years of experience as a BI Developer. She worked on different reporting tools, databases and have good understanding of data warehouse concepts. Her previous experiences were in Healthcare and Banking domain. She started learning Tableau after a long career break and instantly got hooked to the creative visualisations in the Tableau community. She loves to create custom charts and loves the flexibility of Tableau to create stunning visualisations. She also dived into data analytics and found bringing meaning to raw data and finding new insight interesting. She came to know about Data School while doing Makeover Monday projects and found it the perfect opportunity to work on real life situations. In her free time, she loves reading and painting.