Semester of Graduation
First Major Professor
Second Major Professor
Master of Science (MS)
Data has a wide impact in all our lives today. Every little piece of information is being put to use – it is being analyzed, trends are looked for and prediction models are built. A very important step in this process is the Visualization of available data. This provides insight and a better comprehension of data at hand for the audience. It is not just limited to domains that move towards machine learning, but also a lot of corporate companies need the aids of data & visualization to analyze metrics such as the performance of a product, its impact over time, etc. Said that, how could one analyze and visualize their data? There are plenty of tools & languages in the market to do the task for you. To name a few of the well-known ones – PowerBI, Tableau, Google Data Studio, Alteryx, R, Python, Highcharts, D3. Each of them is best suited for use based on the amount of data, the purpose (Pure Visuals vs Combined Analytics), programming expertise, etc. This report focuses on three of the above, namely – R, Tableau and Highcharts. These tools have been chosen for analysis because they are quite popular and also each one has a varying level of difficulty and skill set requirements. I did not want to include tools or languages such as D3.js or SVGGraph owing to my prior familiarity with those – which might add bias to the comparisons.
Venkatachalam, Abirukmani, "Evaluation of Data Visualization Tools" (2019). Creative Components. 272.