About this course
Overview of the principles of the gestalt theory of visual perception and their role in data visualization and data storytelling.
Pre-attentive visual properties and how to use them in a data visualization.
Best practices for color usage and overview of qualitative, sequential, and diverging color palettes and color themes.
How to select colors to ensure accessibility and a list of resources to select color schemes for a better data visualization.
Layout considerations and an overview of the inverted pyramid and Z layout patterns.
When to best use bar graphs, their history, different types of bar graphs, and data visualization best practices for bar graphs.
When to best use line graphs, their history, different types of line graphs, and data visualization best practices for line graphs.
Going more in depth into the chart which is vastly disliked by data visualization experts, but adored by a wide audience.
Exploring the statistician's favorite chart, when to use the scatter plot and what to watch out for, its history, different types, and data visualization best practices for scatter plots.
The general considerations we should think about when creating a data story and the data visualizations accompanying it.
Learn how to craft your craft your data story, including the style and story type, questions, structure and toolkits that you can use.
How do you choose the right visual? Here are the considerations for answering this question.
Data visualization choices if you are comparing values against each other.
Data visualization choices if you are showing something over time such as a trend over time.
Data visualization choices if you want to focus on relationships, the correlation or connectedness of your data points.
Data visualization choices when you are showing composition, parts that make up something, or a hierarchy that you want to emphasize.
Data visualization choices when you want to show the distribution, how frequent or scattered some data points are.
Data visualization choices when you want to show data points along a space construct such as a map or a floor plan.
Looking at some wicked different types of charts and strategies that can aid us when we visualize our data.
Looking at some examples of what are some good data visualization options for the questions asked.
A quick review and wrap up with an example of a "scandalous" chart.
Here are some resources if you're looking for a starting point on how to choose a chart based on what you're trying to show.
The data analyst journey of Lluvia Meneses, lessons learned along the way, and reasons to become a data analyst and data storyteller.
The story and journey of Andrew Drinkwater, the president and co-founder of Plaid Analytics.
Advice on how to stand out from the pool of job applicants and useful tips on securing your next data job.
How do you convince others to adopt data visualizations and other useful tips.
Recommendations on how to make the most out of your school experience to help you out in your future career.
Examples and steps on how you can modify your resume to showcase your data storytelling skills.
Here are some examples of how sometimes breaking the rules of best practices for data visualization, can result in a better data story, while still keeping the integrity and reality of the story.
Here is the criteria that you should consider for selecting a data visualization tool to adopt and use.
Data visualization criteria that will influence your tool selection.
Criteria for the overall tool for better usage and management.
Resources that you can use for typography, images, and supporting graphics in order to enhance your data visualizations.
Here are some resources that you can use if you are in need of data for your data visualizations and data stories.
Here are some tips and tricks for mastering the art of storytelling and more.
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