Using data visualizations effectively and correctly is a part of building a data-driven culture in your team. Data visualization creates accessible, understandable, and effective graphic representations of data to help teams understand the patterns and trends in their data and make data-driven decisions. In this course, you will learn about the fundamentals of data visualization, why it is important, and how data visualizations can be useful to your team. You will also explore different types of data visualizations, their use cases, and how to interpret them. Finally, you will discover how to select appropriate tools and visualizations. Upon completion of this course, you'll be able to define the fundamental concepts, types, and uses of data visualization.

Visual designs play an important role in the presentation of data. Understanding and implementing visual design principles can help you build data visualizations that effectively communicate the message and make an impact on the target audience. Through this course, learn visual design principles and how to apply them to data visualizations. Explore elements and best practices for designing compelling visuals. Next, learn how to design effective visuals using contrast and position, as well as sizing and grouping visualization items. Finally, discover how to arrange items, use legends, address data set gaps, and use color for visualizations. After course completion, you'll be able to outline and apply visual design best practices to visualize data.

One of the challenges of data visualization is recognizing and avoiding misleading visuals. These and other common mistakes make data visualization less effective and can lead to incorrect conclusions. Through this course, learn about misleading statistics and visual distortions. Examine some common data visualization mistakes, including data overload, interchanging charts, and the use of color, as well as how to recognize and correct them. Next, explore examples of deceiving statistics, visual distortions, and graphs and how to avoid being misleading. Finally, learn about omitting data, improper extraction, and correlating causation. After course completion, you'll be able to avoid mistakes when visualizing your data.

Data storytelling lets you set up and reveal key results quickly and in an organized fashion. It is a great way to make findings impactful and meaningful for an audience. Through this course, learn about data storytelling and how it can help elevate your data visualizations and create impactful narratives for an audience. Explore the theory and purpose behind data storytelling and how to contextualize and refine insight. Next, discover how to engage with an audience and put together an outline. Finally, learn how to plot data points to a storyboard and format a story for delivery. Upon completion, you'll be able to outline elements of data storytelling and apply them when presenting data.