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Olympics, as we all know is the biggest sporting event on our planet with over 200 countries across the world participating in it. Being an ardent fan of this mega-carnival of sports, i was curious to analyze few aspects related to the Olympics history and hence i chose the data sample ‘Olympics Data’ provided by SAP for my analysis. The dataset contains history related to all the Olympics from 1896 to 2008. Unfortunately, it doesn’t have data related to Olympics 2012. So, my analysis does not include details of 2012 London Olympics. 🙁

To begin with, I wanted to find answers to my following queries related to Olympics:

1. Which country has won the maximum number of medals?

2. Which country and city has hosted the Olympics maximum number of times?

3. In which sports maximum medals had been distributed?

4. Who are the top 10 Olympic athletes of all time?

5. Gender gap in participation and medals won in this mega event.

6. Athletes of which country had maximum participation in Olympics?

Having used SAP Lumira to “Analyze Crop Production in India” earlier, I was confident that I will be able to find answers to all my questions with the help of SAP Lumira. The ‘Olympics Data’ dataset contained information regarding the host country, years in which Olympics was organized and the details related to the medals i.e. the athletes, events, sports, country they belonged etc. as shown below:

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After acquiring the data, i started my quest to find answers to all my queries.

1. Which country has won the maximum number of medals?

To find this, i used the “Tag Cloud” visualization as below:

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From this visualization, it was clear that USA had won the maximum number of medals. To see the number of medals won by any of these countries, I could hover over the country name and find its medal count.

From this chart, i found answer to my 1st question but now i had couple of more queries:

i) Which are the events in which USA have won maximum medals?

ii) Since the number of gold medals won in Olympics decide the ranking of the country, i wanted to find total number of gold medals won by USA and other leading countries in Olympics.

For finding answer to query i), i plotted a “3D Column chart” to view the 10 events in which USA have won the maximum number of medals over the years. For this, I ranked 10 values of the ‘medal_count’ measure and put a filter on ‘Country’. It generated the following visualization:

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It was clear from this chart that:

a) Over the years, USA has won the maximum medals in the BasketBall event.

b) In a particular Olympics, USA has won the maximum medals in the Football event in the year 1904.

ii) Comparison of Gold medals won by leading countries:

I created a “Pie Chart” visualization of the top 10 countries with a filter on Medal type as ‘Gold’. I could easily determine from this chart that USA had won the maximum number of gold medals followed by Soviet Union, Great Britain, Italy and Germany.

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2. Which country and city has hosted the Olympics maximum number of times?

As the sample data did not contain host country as an attribute, i created a geographic hierarchy by name on the host ‘city’ attribute. It’s one of the greatest features of Lumira that while creating a geographic hierarchy, it generates all the hierarchical levels up-to the desired level e.g. for hierarchy of city, it generates levels of country, region, sub-region and city.

I created a “Geo Pie Chart” for the same using country from the geography created above as the ‘Geography’ dimension and city as the ‘Overlay Data’ as displayed below:

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From this chart, i could easily determine that USA is the country that has hosted Olympics maximum times but it is bit difficult to determine the city that has hosted this mega event the maximum no. of times. I could have done that by creating a “Geographic Bubble Chart” but i wanted to determine both the host city and country that had hosted Olympics maximum times with the help of a single visualization.

So, I created a “Tree Map” visualization with the country from the geography created above as the Area name and ‘Year_Count’ measure as the Area Weight to determine the city and country hosting Olympics maximum number of times as shown below:

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I could easily conclude from this that USA is the country which has hosted Olympics maximum number of times(4 times) and Los Angeles, Paris, Athens and London are the cities that have hosted it maximum number of times(2 times).

3. Which sports had maximum medals associated with it?

For this, i created a “Column chart” visualization to display the top 10 sports and the discipline to which they belong as shown below:

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It could be easily inferred from this that the maximum number of medals have been distributed in ‘Athletics’.

4. Who are the top 10 Olympic athletes of all time?

Finally, i came to the question whose answer i wanted to know most curiously – Who are the top 10 Olympic heroes of all time. I found the answer to this with the help of a “Line chart” as shown below:

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From this visualization, it could be easily concluded that ‘Larisa Latynna’ is the best athlete with maximum number of Olympic medals and ‘Michael Phelps’ has the maximum number of Gold Medals – the 2 legends of the Olympics at the top 🙂  

5. Gender wise Analysis of Participation and Medals won

Now, I wanted to check the Gender gap in the participation and medals won in Olympics. I could determine both of these by using the ‘Trellis’ feature of Lumira in a “column chart”. I used ‘Medal Count’ and ‘Athlete Count’ as measures, ‘country’ as the Legend color and defined ‘gender’ in the ‘Columns By’ property of the Trellis section as shown below:

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I could easily figure out from this chart that the number of female athletes participating and winning medals in Olympics is much less than their male counterparts. Their is a huge gender gap.

Also, i got answer to my last question i.e. athletes of which country had maximum participation in Olympics with the help of this visualization 🙂 USA has the maximum male and female athletes participating in Olympics.

Thus, i was able to find answers to all my queries related to Olympics quite easily using the features of SAP Lumira. I hope that you like this blog and I am looking forward for your comments and suggestions..

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