No, I haven’t ever created a visualization of data. I found this famous “Hierarchical Structure of Internet” which was a study that observes about the way Internet is organized, in terms of both i.e. Structure and connectivity. It demonstrates how the central core of the Internet is comprised of about 80 core nodes and 70 % of other nodes continue with their functionality via peer-to-peer connections even if the core nodes fail. The picture below demonstrates the hierarchical structure of the Internet, based on the connection between individual nodes. As, from “Fig. A” three distinct regions are apparently, a mantle-like mass of peer-connected node; an outer periphery of isolated networks, and the inner core of the highly connected network. The conclusion drawn from the below visualization is that overall capacity if the Internet could be improved by using peer-to-peer communication and make it run smoothly. Tableau is one of the most frequently used data visualization software for all good reasons. In big data operations which process very fast changing and huge dataset, Tableau is well suited for handling such data. Its integration with much more advanced database solution like AWS, My SQL, Hadoop etc make its one of the optimum choice.
Fig. A1 Fig. B3
Ans. 3 The Dataset of Global Food Prices with monthly market food price across developing countries could be used to visualise the impact on the food price in response to, weather conditions or currency fluctuation. The dataset consists of over 740k rows of prices obtained in developing world market for various group, which include goods in local currency, quality of good, and month recorded. Global food prices changes could impact in large population Shift and cause scarcity of food. Price change is an important aspect for consideration by policy makers to monitor weaken the food supply. Hence visualising the price shift in food item in context with different parameter will help to keep a check on various events. It might be visualised using Horizon graph chart type, i.e. Compact the area chart by slicing it horizontally and the shifting the slices to baseline zero 3. For Example, in Fig. B 3 to represent higher absolute values darker colours are used, and addition information with the filled trend line can be observed.