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Data Visualization Foundations

In this two day workshop you'll learn how to present information effectively using interactive data visualizations. You'll gain critical data visualization literacy, and gain experience building your own visualizations.

Who should join?

• Designers & developers interested in effective presentation of data.

• Product managers seeking to leverage data visualization.

• Data scientists who want to push beyond static statistical graphics.

• Anyone interested in data visualization.

Day 1: Theory

• Why Visualize? When to use, and not to use, data visualization

• Input: data and tasks/questions

• Data: types of attributes (Nominal, Ordinal, Quantitative)

• Marks and Channels: X, Y, Color (Hue, Luminance, Saturation), Size, Faceting (small multiples), and more

• Visual Encoding: Mapping data to marks and channels effectively

• Using Color in Visualization: Categorical Schemes, Continuous Schemes, Diverging Schemes

• Data Reduction: Taming “big data” for visual presentation, using aggregation, filtering, or sampling

• Brief summary of what’s possible with interactive visualization.

Prerequisites for day 1

•  Basic understanding of data

•  Desire to leverage data visualization

•  Be sure to bring your laptop

Day 2: Practice

• Hands-on programming with Web Technologies, including libraries D3.js, React, and Vega.

• Forking & modifying visualizations

• Implementing interaction using unidirectional data flow & dynamic state

• Interactions in a Single View:

      • Select (hover, click)

      • Highlight

      •  Brush

      •  Pan & Zoom

      •  Filter (slice)

      •  Change Encoding (select columns to visualize)

•  Interaction Patterns with Multiple Views

      •  Linked Highlighting

      •  Overview-Detail

      •  Details-on-demand

      •  Linked Navigation

      •  Dynamic Layers

Prerequisites for day 2

•  Familiarity with web technologies

•  A GitHub account

•  Bring your own (public) dataset to visualize!

What won’t be covered

•  Fundamentals of JavaScript, CSS and HTML

•  Machine Learning, Artificial Intelligence