Introduction to Data Visualization

Our approach to data visualization is in keeping with the broader guiding principles of Spark, especially:

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)

In addition to providing clarity, successful data visualization informs users and provides insights necessary to make decisions.

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.

Depending on the application there is a variety of data visualizations to choose from, click on one to explore:

Bar Charts

Pie and Donut Charts

Gauges

Line Graphs

Color should be used in a manner that is consistent with the Spark Color Palette, click here to see all Data Visualization Color Palettes.

Sequential

Divergent

Qualitative

Status

The following page illustrates a common layout for data visualizations and the location for controls and information that appears alongside most charts and graphs.

Data Visualization Annotated illustration

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.

Some additional variations include:

(Click image to open full resolution)