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Data visualization has been viewed by many disciplines as a modern equivalent of visual communication. It finds interpretation across many and is not owned by anyone fields. It involves the study and creation of the visual representation of data, which means that information that is being abstracted in some schematic form includes variables or attributes for the units of information. The important goal of data visualization is to communicate information efficiently and clearly to users via the plots, statistical graphics, tables, information graphics, and charts selected. Effective visualization helps users in reasoning and analyzing evidence and data. It makes complex data more understandable, accessible and usable. The users may have particular analytical tasks, such as understanding causality or making comparisons and the design principle of the graphic that follows the task. The Tables are generally used where users look-up a specific measure of a variable, whereas, charts of various types have been used to show patterns or relationships in the data for one or more variables. Data visualization is generally a science and art. The rate at which the data is generated has increased and is driven by an increasingly information-based economy. Data created by an expanding number of sensors in the environment and an internet activity such as traffic cameras and satellites are referred to as “Big Data”. Analyzing, Processing and communicating this data present a variety of analytical and ethical challenges for data visualization. Data visualization refers to the techniques that are used to communicate information or data by encoding it as visual objects which is contained in graphics. The goal is to communicate information efficiently and clearly to users. This is one of the steps in data science or data analysis. According to Friedman (2008) the main goal of data visualization is to communicate information effectively and clearly through graphical means. This doesn’t mean that data visualization needs to look beautiful or boring to be extremely sophisticated or functional. According to Professor Edward Tufte users of information, displays are executing particular analytical tasks such as determining causality or making comparisons. The design principle of the graphics information should show the comparison or causality and support the analytical task. Edward Tufte in the year 1983 in his book, The Visual Display of Quantitative Information outlines principles for effective graphical display and graphical display in the following passage. The Graphical display should
- Be closely integrated with the verbal and statistical description of a data set.
- Serve a reasonably clear purpose: exploration, description, tabulation or decoration
- Reveal the data at several levels of details from a broad overview of the fine structure
- Encourage the eye for comparing different pieces of data
- Make large data sets coherent
- Present many numbers in a small space
- Avoid distorting what the data says
- Induce the viewer to think about methodology rather than substance, graphic design, the technology of graphic production or something else
- Show the data
The Graphics reveal data. Graphics can be more revealing and precise than conventional statistical computations. Learn from experienced tutors to improve knowledge and grades in that particular subject. Assignment help service provides a chat room for Data Visualization assignments meant for students and tutors.
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