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Data Geek Challenge III : Natural Disasters

Hi All,

I have joined Data Geek Challenge III to showcase the Natural Disasters and Disaster Plan by using best tool like SAP Lumira  for Data Visualization.

Allegiance: House of Spirits.

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I care for the Social Good, so I have focused on Natural Disaster. Natural Disaster is a major harmful event resulting from natural processes of the Earth causes widespread destruction, loss of life or lots of collateral damage, it might be earthquakes, flooding, volcanic eruption, landslide, hurricanes etc, and I want to share this information to all because Natural disasters cannot be prevented, but measures can be taken to eliminate or reduce the possibility of trouble. Hence I have decided to uncover information with innovative data visualizations by charts and with emerging trends.

Source of Data: Wikipedia information on Natural Disasters by Death Toll

The below Tag Cloud Chart display Death Toll by Location and China holds the highest Death Toll. Death toll of China is higher than the previously estimated worst natural disasters in history.

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In a single Heat Map Chart, end user can able to visualize the Natural Disaster cause by Location.

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In this below 3D Column Chart, Top Ten Worst Natural Disasters where measured by death toll. From this chart, Flood and Earthquake are the major natural disasters which caused environmental effect and/or human loss and frequently incur financial loss.

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This below Funnel chart, display the Top five worst Natural Disasters affected Location, and the 1931 China floods were a series of floods that occurred in the Republic of China. Turkey location sticks on bottom of the five worst Natural Disaster affected Location.

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From the below Network Chart, the Natural Disaster causes are acts like servers and the locations are hubs which are routed by the routers to have a clear information on which Natural Disaster occurrence is most.

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We will have a fair idea by now, by visualizing data on few specific charts on Natural Disasters by Death Toll. SAP Lumira, help us to explore data for this scenario which leads us to think about the basic security and appropriate actions like preparedness, warning, prevention at all points to save human life and to avoid or reduce the potential losses from hazards during next iteration of the Hazards Cycle.

Hence, before you travel to China, it is recommended that you check the weather conditions  😉

I hope you will like this blog and am looking forward for your valuable comments and suggestions.

Thank you for reading this Blog 🙂

With Regards,

Rajeswari. S

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      1 Comment
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      Author's profile photo Former Member
      Former Member

      Thank you for producing this collection of stories, very interesting subject matter. It would be great to also see the years associated with each natural disaster.

      The perspective is staggering in the funnel chart. It would be nice to see the data values of what's being charted here. Also, are the values correct on the heat map legend? Be sure to touch up the headings on each screenshot. (Please also submit larger screenshots so they can be enlarged when clicked).

      Would like to see even more charts that show counts by year, continent, season, month, correlation of death toll to financial loss (in a scatter plot), and something related to disaster trends that would infer predictability.

      Again, excellent choice of subject matter. This is a good start.