Exploring Data Analytics

    World Cup final is getting closer and the world is awaiting for a winner. Here is a fun way of reliving the moments from the first 100 goals scored in the tournament. I have used Tableau to create the visualization where we can search for a Scorer Name or the Team name and see the corresponding goal location on the football pitch. A dot on the pitch indicates the relative position from where the goal was scored. Interesting to note the self goals on the left side.    Look out for Ronaldo's hattrick and Messi's 100th goal in the tournament. Here is the Tableau link.  WorldCup2018     Dataset: FreedCamp. This visualization can be further improved by adding all the goals from all World Cup matches since 1930 , and further add other event types like Fouls, Yellow and Red Cards etc.

    Last week I stumbled upon one of my research assignments using Parallel coordinate plots(PCP) which I did last year. When the data has two dimensions it can be easily plotted using a bar chat or a scattered plot. But as the dimensions increase it is difficult to plot them as the chart gets distorted. I found this tool called Tibco spotfire which readily allows to explore PCP data and many more options. Lets see them below.     For example: there are 5 cars and each car has 5 features to be compared then we can use Bar charts. Radar charts can also be used to plot the spatial area between these dimensions.      Now consider that there are 1000's of car and each car has many attributes. Radar charts cannot be used here as the visualization would be difficult. We can use parallel coordinate plots. Parallel coordinate plots are used for plotting multi variate numerical data. Here each feature is represented by a line between two axis instead ...