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Develop Visual Models • Data visualization is the graphical representation of information and data

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I have already completed most of the work. I need someone to go ahead and Add more to my part 3 and part 4. at least one page for each. I can provide you the instructions and documents upon matching, Thanks.
Part 3, Information Visualization Report (Part 3 of 4)
ET
Submit a report (No minimum or maximum length) showing your visualizations of your data and information.
Interpret the visualizations and describe how the results reflect your initial hypothesis. Make sure to establish the
foundation for your visualization, such as audience needs and requirements. Also, describe why you selected the
visualization techniques you used. Consider the following:
1. Develop Visual Models
• Data visualization is the graphical representation of information and data. By using visual
elements like charts, graphs, and maps, data visualization tools provide an accessible way to
see and understand trends, outliers, and patterns in data.
• Data visualization tools and technologies are essential to analyze large or complex
AIT-664
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data/information sets in support of data-driven decisions.
• Data visualization helps the identification of trends, correlations, and outliers. Many forms of
data and information are difficult to interpret without some form of visualization. Multiple visual
“views” may aid in identifying data and information relationships.
Part 4, Project Recap & Lessons Learned (Part 4 of 4)
Due week 8, ET
Submit a summary of your overall analysis, including your initial requirements and hypothesis, data acquisition,
data preparation, information modeling, and information visualization. This final report should encapsulate your
full semester’s effort. Report on the effectiveness of your analysis and whether you met your initial goal of
demonstrating your hypothesis. Explain the challenges you faced, what went right and what went wrong, and
what you might have done differently to improve on your analysis if you were to do it again. Consider the
following:
1. Report Results
• Restate your initial hypothesis.
• Report your analysis results.
• Describe your overall approach to your analysis effort.
• Determine how effective your analysis was.
• Describe if and how you demonstrated your hypothesis or the null hypothesis.
• Describe any lessons you learned from the analysis project

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