San Jose State University Data Visualization Technique Responses

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Computer Science

San Jose State University


Answer 1

Data visualization is a technique in where huge amounts of data is collected and with some tools based on analytics get a different kind of graphical type of representation. In this way the business can be viewed better in this kind of way. The business with huge amounts of data don’t know what to do with that (Sahay, 2017). There are different types of tools in data visualization. Some examples are Tableau, Microsoft Power BI, Excel, and Google charts. The different forms of graphical representations are charts, Pi charts, histograms, maps etc.

The key component of data visualization is determining what the company really wants and determining if there is any need of doing this technique (Sahay, 2017). The second component is determining where the data is taken and how it will be used to know how the business doing. This component gives what this will do to the business. The last component is understanding where to get data from and which format the data is in i.e., structured, or unstructured.

This course can give different approaches on how data visualization works. In this course can learn about how datasets are used in bringing the best in the visualization. This course will give different types of tools learning and understanding which can be used in the development of the student future in data visualization. This can be used in making business better.


Sahay, A. (2017). Data visualization. Business Expert Press.


Answer 2

Definition of data visualization

Data visualization is the process of representing and presenting data to leverage understanding. The process involves using the graphical representation of data to make understanding seamless (Kirk, 2019). Data visualization adopts visual tools such as graphs, charts, maps, etc., to make complex data seamless to understand and derive meaning. In the wake of big data, data visualization is a vital tool that enables decision-makers to comprehend and analyze complex data for effective decision-making. The major advantage of big data is that it makes understanding complex data seamless, leading to speedy decision-making.

Component of data visualization

There are three major components of data visualization, which include perceiving, interpreting, and comprehending data. At the perception stage, the audience tries to understand what they see (Kirk, 2019). It involves making simple cognitive functions and asking a simple question about what they can see. At the interpreting stage, the audience tries to get the meaning of what they see. The last component is comprehending, which involves getting the real meaning from what they have interpreted. It is important to note that different audiences may comprehend the visualization differently based on their understandings.

Techniques I want to learn from the course

Data visualization concepts are vital in the current big data era. Organizations are generating massive amounts of data from which they struggle to get meaningful revenue (Kirk, 2019). Thus, I aim to acquire competent data visualization skills to facilitate the seamless analysis and interpretation of big data. I want to learn color skills, graphs, charts, and other critical data visualization tools, ideal for my future career journey.


Kirk, A. (2019). Data visualization a handbook for data-driven design. Los Angeles, CA Sage. ISBN 978-1473912144

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Explanation & Answer

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Response 1
Hello, I enjoyed reading your post; however, let me expand on the topic. Data visualization
entails the presentation of data in a visually appealing way to make it easy to understand. When
data is presented visually, it becomes possible to grasp what is presented and correlate with past
data easily. Excel is one of the best data visualization tools bec...

Very useful material for studying!


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