In this course, we will cover the basics of visualization and how it fits into the Data Science workflow. We will focus on the main concepts behind the purpose of visualization and the design principles for creating effective, easy-to-communicate results. You will also set up your Tableau environment, practice data loading, and perform univariate descriptive analysis of the S&P 500 stock sectors.
Data Visualization Best Practices
Data Visualization Best Practices
This course is part of Use Tableau for Your Data Science Workflow Specialization
Instructors: Julie Pai
4,838 already enrolled
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Gain insight into a topic and learn the fundamentals.
3.9
(14 reviews)
8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
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Assessments
4 assignments
Taught in English
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This course is part of the Use Tableau for Your Data Science Workflow Specialization
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There are 4 modules in this course
Visualization is a crucial skill for data analysts across all disciplines. Viewing data graphically often provides greater intuition than by using statistics or mathematics alone. In this module, we’ll explore the fundamentals of visualization and discuss how visualizations can achieve better insight into data as well as effectively communicate results and conclusions.
What's included
1 video5 readings1 assignment1 discussion prompt
To create effective visuals, analysts must understand and be able to explain why specific graphical elements must be included, eliminated, or modified. In this module, we’ll investigate why certain questions are best answered by specific visual cue patterns, discuss which psychological perception theories should be considered during the construction of data visualizations, and cover the universal framework for representing visual data, the grammar of graphics.
What's included
1 video3 readings1 assignment1 discussion prompt
Univariate visualization methods apply the grammar of graphics to the representation of a dataset’s fundamental properties and structures in terms of single variable mappings to visual encodings. In this module, we’ll explore specifics for how to view the data and what to visualize and discuss what mapping of data is best suited for highlighting and extracting insights from the data.
What's included
1 video3 readings1 assignment1 discussion prompt
Instead of reinventing the wheel with every visualization, analysts use several common chart types so there is no ambiguity about the decoding and interpretation of the data. In this module, we'll explore some standard tools and techniques that are used to prepare a fully crafted set of visualizations for the purpose of storytelling. Before completing this module, you will use Tableau to conduct a univariate analysis to sample data, compare dimensions vs. measures, and practice linking visualizations.
What's included
1 video4 readings1 assignment1 peer review
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