Visualization of Large-Scale Aqueous Solubility Data Using a Novel Hierarchical Data Visualization Technique

2006 ◽  
Vol 46 (3) ◽  
pp. 1054-1059 ◽  
Author(s):  
Fumiyoshi Yamashita ◽  
Takayuki Itoh ◽  
Hideto Hara ◽  
Mitsuru Hashida
Author(s):  
Nirmit Singhal ◽  
Amita Goel, ◽  
Nidhi Sengar ◽  
Vasudha Bahl

The world generated 52 times the amount of data in 2010 and 76 times the number of information sources in 2022. The ability to use this data creates enormous opportunities, and in order to make these opportunities a reality, people must use data to solve problems. Unfortunately, in the midst of a global pandemic, when people all over the world seek reliable, trustworthy information about COVID-19 (Coronavirus). Tableau plays a key role in this scenario because it is an extremely powerful tool for quickly visualizing large amounts of data. It has a simple drag-and-drop interface. Beautiful infographics are simple to create and take little time. Tableau works with a wide variety of data sources. COVID-19 (Coronavirus)analytics with Tableau will allow you to create dashboards that will assist you. Tableau is a tool that deals with big data analytics and generates output in a visualization technique, making it more understandable and presentable. Data blending, real-time reporting, and data collaboration are one of its features. Ultimately, this paper provides a clear picture of the growing COVID19 (Coronavirus) data and the tools that can assist more effectively, accurately, and efficiently. Keywords: Data Visualization, Tableau, Data Analysis, Covid-19 analysis, Covid-19 data


2018 ◽  
Vol 224 ◽  
pp. 02071
Author(s):  
Dmitrii Voronin ◽  
Victoria Shevchenko ◽  
Olga Chengar

Scientific problems related to the classification, assessment, visualization and management of risks in the cloud environments have been considered. The analysis of the state-of-the-art methods, offered for these problems solving, has been carried out taking into account the specificity of the cloud infrastructure oriented on large-scale tasks processing in distributed production infrastructures. Unfortunately, not much of scientific and objective researches had been focused on the developing of effective approaches for cloud risks visualization providing the necessary information to support decision-making in distributed production infrastructures. In order to fill this research gap, this study attempts to propose a risks visualization technique that is based on radar chart implementation for multidimensional data visualization.


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