Introduction to Data Visualization
Our Approach
Our Data Visualization approach is consistent with the broader guiding principles of Spark, especially the following:
Simplify users' lives through modern, intuitive interfaces.
When illustrating complex data relationships, the goal is to provide clarity. We have adopted a display that minimizes clutter, promotes focus and strives to achieve an “efficient communication of complex quantitative data.” (Edward Tufte)
Empower users through intelligent, personalized displays.
In addition to providing clarity, successful data visualization informs users and provides insights necessary to make decisions.
The following recommendations will help you align with the two principles above:
Keep it Simple
Strive for an immediate understanding of what the data represents.
Eliminate Redundancy
Do not include multiple visual affordances for the same information.
Focus on the Data
Keep controls and additional content to a minimum. Use progressive display to provide access to detailed content.
Give Users Control
Include effective and intuitive controls for allowing users to configure the data.
Chart Types
Depending on the application there is a variety of data visualizations to choose from, click on one to explore:
Color Usage
Color should be used in a manner that is consistent with the Spark Color Palette. View all Data Visualization Color Palettes here.
Controls & Layout
The following image illustrates a common layout for data visualizations and the location for controls and information that appears alongside most charts and graphs.
Layout & Information Hierarchy
The sequencing of elements may vary based on the information hierarchy of your page. For example, the KPI Bar should appear at the top of the page if it does not change based on the tagging control above it.
Each of the layout examples below are available in the Spark Data Visualization Sketch / Figma files.
(Click image to open full resolution)
