Data Visualization

Data Visualization

Data visualization refers to the practice of presenting numeric data in graphical form. The goals are to present a simple, meaningful and lively way of displaying information. Data visualization is an effective tool that has a lot of potential uses in businesses, marketing and social media. Unfortunately, a lot of people struggle to design data visualizations so they can make sense and deliver the intended message in the right way.

Data visualization is becoming more prevalent as tools like Tableau have helped businesses visualize their data more effectively than ever before. The below infographic displays the benefits of data visualization and how they can help your business. Through data visualization, businesses can easily identify trends, patterns and otherwise abstract ideas. For example, a social network’s sign-up forms often contain fields that ask for information on age, gender and location. By graphing that data over time, a business could identify changes in the number of users at different age groups or compare their overall response to industry-wide trends.

Data visualization can also help guide businesses’ decisions by providing them with visual feedback on various metrics. With this data visualization, it’s easy to see patterns. Even with a large number of data points, it is easy to identify the most useful data. Designing effective data visualizations will likely take some practice, because it’s easy to make mistakes. However, the biggest issues businesses may encounter are the result of poor design — not poor information. Businesses may need a seasoned skillset and experience in order to effectively create good visualizations.

Trends in technology have contributed to more interest in data visualization over time as people experience gained access and ability to create more robust visualizations through online platforms such as Tableau and Tableausoftware.com. This wide access has improved reliability and quality for common users of data visualization.

Reference

Best practices of data visualization – Illustrator Video Tutorial | LinkedIn Learning, formerly Lynda.com. (2022). Retrieved 11 April 2022, from https://www.linkedin.com/learning/data-visualization-best-practices-14429760/best-practices-of-data-visualization-14398183

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Data Visualization

Data Visualization

DATA REPRESENTATION

(1). FORENSIC DESIGN ASSESSMENTS

This task relates to a sequence of assessments that will be repeated across Chapters 6, 7, 8, 9 and 10. Select any example of a visualisation or infographic, maybe your own work or that of others. The task is to undertake a deep, detailed ‘forensic’ like assessment of the design choices made across each of the five layers of the chosen visualisation’s anatomy. In each case your assessment is only concerned with one design layer at a time.

For this task, take a close look at the data representation choices:

Start by identifying all the charts and their types

How suitable do you think the chart type choice(s) are to display the data? If they are not, what do you think they should have been?

Are the marks and, especially, the attributes appropriately assigned and accurately portrayed?

Go through the set of ‘Influencing factors’ from the latter section of the book’s chapter to help shape your assessment and to possibly inform how you might tackle this design layer differently

Are there any data values/statistics presented in table/raw form that maybe could have benefited from a more visual representation?

(2). CHART VOCABULARY: CAPABILITIES

Evaluate your ability to potentially create as many as possible of the chart types presented in the Chapter 6 chart gallery. Go through each chart assigning a score based on the points system (0, 1, 2, 3) described in the ‘Influencing factors’ section at the end of the chapter.

(3). CHART VOCABULARY: THINKING

Building on your data familiarisation and editorial thinking work over the past two chapters, pick one of the subjects you have been looking at and follow one of three different data representation task tracks, referring to the book’s chart type gallery in each case:

Identify a chart type that could be used to display the different editorial perspectives you identified in your brainstorming activity of chapter 4

Identify as many chart types as possible that could show something interesting about the subject in general, though maybe not confined to the data you have been looking at

Force yourself to identify at least 2 chart types from each of the 5 classifying chart families (CHRTS) that could portray different interesting editorial perspectives about this subject, starting with the data you have and then considering what additional data you would need to fulfil this activity

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Data Visualization was first posted on April 21, 2019 at 11:06 pm.
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