It is important to have a logical order to your data visualization, this involves having a discrete beginning, middle, and end. The information should be organized in a way that is easy for the audience to understand and follow. One way to think as a designer is to focus on the layout and overall aesthetic of the data representation, such as using colors, typography, and images to make the data more engaging and easy to understand.
As a data analyst, think like a designer even though you are not one. When thinking as a designer, a data analyst should focus on creating visually appealing and informative data representations that effectively communicate insights and conclusions to the audience. One major quality of designers is that they are mindful of their audience, they want to create visualizations that are appropriate for the audience and the message they are trying to convey. They also ensure that the data representation is easy to navigate and interact with – User Experience. This could include designing interactive elements such as hover-over text, filtering options, and zoom functionality to make it easier for the audience to explore and understand the data. As always considering the audience, the context, and the message of the data, and using design principles and techniques to effectively communicate insights and conclusions in a visually appealing and informative way are the most important aspects of a good visualization.
In telling a compelling story an analyst may choose to use a line chart to represent time series data, or a heat map to represent geographic data. Your main focus will be on creating visually appealing and informative data representations that effectively communicate insights and conclusions to the audience. For example, if you are displaying data on sales, it may make more sense to organize the information by date or by product category, rather than randomly displaying the data. Additionally, it is important to consider the context in which the data is being presented and the audience for which it is intended, as this can also affect the logical order of the information. The goal is to make it as easy as possible for the audience to understand and extract insights from the data. Understanding your audience and factoring their expectations in your storytelling will go a long way to validating their convictions to the result of your analysis.

Leveraging the categorical data in charts
Realizing that analysts frequently make use of charts in visualizing data is a key factor to consider when preparing your report and knowing which chart fits a particular subject is vital. Ordering categorical data in a horizontal bar chart refers to organizing the data in a specific way to make it easier for the audience to understand and extract insights from the chart. When creating a horizontal bar chart to display categorical data, one way to leverage the order is by arranging the bars in a logical order, such as alphabetical or numerical order. This makes it easier for the audience to locate specific categories and compare them to others. Another way to leverage the order is by arranging the bars in a way that highlights specific patterns or trends in the data. For example, if the data represents sales by product category, you could order the bars from highest to lowest sales, which would make it easy for the audience to see which categories are performing well and which are not.
Additionally, you can also sort the data in a way that makes the chart more visually appealing, for example, by alternating the color of the bars or by making use of a color scale to represent the value of each category. Leveraging the order of categorical data in a horizontal bar chart involves organizing the data in a logical and meaningful way that makes it easy for the audience to understand and extract insights from the chart.

Below is the summary of the best practices and guidelines to deliver artistic graphic that makes the information easier for the audience to understand, remember and stay convinced.

1. Understand the context of the issue to communicate in the report.
2. understand the data and figure out what might interest the audience using direct images, storytelling strategies, and sound design principles to produce data visualizations that are simple to comprehend and retain.
3. Comprehend your audience and the message you want to deliver before developing a visual report. This will enable you to make the visualization more pertinent and interesting for the viewer.
4. Using an effective design concept such as color, font, charts, outline, and typography, to direct the viewer's eye and interest to crucial information is another aspect I learned from the book.
5. Create a visual hierarchy and direct the viewer's focus to the most crucial details.
6. Remember to keep it simple and avoid information overload by trimming out superfluous details, emphasizing important facts, utilizing strong design concepts, and unambiguous labeling.

It is crucial to establish trust with the audience by being open and honest about the data and techniques used to generate the visualization. Providing context for the data and being transparent about data sources, assumptions, and limits are part of this. The value of openness and confidence in data visualization and storytelling is paramount.