CASE STUDY:QS WORLD RANKING CASE STUDY
Introduction QS World University Rankings is a portfolio of comparative university rankings compiled by global higher education analyst Quacquarelli Symonds (QS).
As a Engineering pursuing student I wanted to analyse data about all the colleges that offer degrees in related fields.I found out about the QS world ranking data set from Kaggle and then started cleaning it in Microsoft excel.Then loaded the data in big query to run some SQL commands on it
How many colleges are present all over the world?
- when we run this simple sql query on the dataset of qs world ranking we were able to find out the count of colleges in each country
SELECT COUNT(DISTINCT Institution_name) AS College_Count from <your data table> GROUP BY Country ORDER BY College_Count DESC
(sql is not case sensitive so any case would work)
- Then we put the result in Tableu to generate this beautiful visualisation of countries with their college count
- Conclusion: USA has the most amount of universities =199
The visualisation shows countries with most colleges with green and least colleges with red
Which college is the best in terms of employement score
- After running this big query we were able to find top 10 colleges along with their countries
SELECT Institution_Name,Country,Employment_Outcomes_Score FROM <Table name> order by Employment_Outcomes_Score desc limit 10
(sql is not case sensitive so any case would work)
- Conclusion: USA has the best employabilty score followed by UK
Thus we are able to deduce that the best colleges for employability are in the US and UK.
Now we plot average of of the employability score of top 10 countries using R
As we can see the colleges in the US do not have the best average Employment Outcomes Score
Reason:There are 199 colleges in the US thus their average does not produce a large average
Reason:There are 199 colleges in the US thus their average does not produce a large average
This is a Dashboard of the final Analysis
Made with ❤️ byㅤRohan Shah