#visualizaton

[martinmurphy3-blog]

There are different types of algorithm that exists for each dissimilar type of data. The classification of algorithms depends largely on the character and function of the data. To perform its best and to express with complete application of all the visualization principles, it is required a distinct algorithm for each data type. There are different types of data. Accordingly there are corresponding algorithms. The pack of data can be classified following its types of variables, volumes, distribution etc. All these play a major role in determining the corresponding algorithm for perfect visualization. This further provides a large spectrum of multitudinous algorithms applicable for selecting, processing, clustering and shaping abstract data.

[datajournalismlinks]

Overwhelming selection with infographics from some of the top graphics desks in the world

[nusightanalyticsadvisory-blog]

Visualization to Insight: Effect of post secondary education

OECD data is used as a mainstay for this work. Twenty countries originally signed the Convention on the Organization for Economic Co-operation and Development on 14 December 1960. Since then fourteen countries have become members of the Organization. For more details please see details on OECD

The visualization is in Tableau public. 

Some insights from this visualization are as follows:

USA has a healthy rate of higher educated people ~ 42-44%

 The rate of completion and rate of entering is greatly reducing which is a obvious threat to the 60% by 2025 target

There seems to be a preponderance of impact of parents education level on the education attainment of students- posing the question of level playing field

The return to private and public education and the lift on top of secondary education is significant, which indicates a healthy need and rewards for students of higher/ tertiary education that should encourage them to enroll in higher education.