Visualisation best practice
First begin with understanding client business, technical and business requirements.
Understand the context of the visualization and audience who we intend to build.
Capture user stories/business problems they are trying to address.
Understand the data model, data analysis and data preparation.
Storyboard/sketch initial prototype to solve the above problems.
Choose an appropriate visual that effectively brings the story live and answer the business
Remove unnecessary elements, keep it clean and simple.
Showcase the visualization to stakeholders, seek feedback and iterate.
Data reconcile to make sure the numbers in the visualization are matching to the numbers in the source.
Unit testing, System testing, UAT, approval and deploying to production.
User training, support and maintenance.
Form follows function: First, we want to think about what it is we want our audience to be able to do
with the data (function) and then create a visualization (form) that will allow for this with ease.
Don’t assume that two different people looking at the same data visualization will draw the same conclusion.
Leverage pre-attentive attributes to make those important words stand out.
Offer your audience visual affordances as cues for how to interact with your visualization.
Highlight the important stuff and eliminate distractions.
Make it legible and clean.
Label and title as appropriate, so there’s no work going back and forth between a legend and the data to decipher what is being graphed.
Whatever data is required for context, but doesn’t need to be highlighted, push it to the background.
Employ attributes like color, thickness, size, position, labeling, text and annotation to emphasize and
de-emphasize components throughout the visual.
If there is a conclusion you want your audience to reach, state it in words.
By: Seraj Alam