Jo's Works - UX / UI - Data Visualization

Data Visualization Simplification

Project summary of how I utilized various methods to simplify the drag-and-drop based, ad-hoc interactive data analytics UI, provided better onboarding experience for novice users, shortened their learning curves, and enabled self-learning and self-service.

Target Users:

Data Producer
Data Consumer
Data Scientist
Data Analyst
Executive

UX Problems of the Previous UI

Two Major UX Pain Points

With the help of my usability researcher, we identified two major UX pain points from our annual UxR benchmark study:
1. The drag & drop interaction paradigm is unclear.
2. The UI controls and workflows are complex.

Personas and Use Cases

As a starting point, even it's an existing product, it's essential to revisit who the target audiences are. Understanding the personas and their use cases helped me better define the real design problems.

Competitors Analysis

Meanwhile, I also investigated some of the dominant ad-hoc data analytics & data visualization products, analyzed their design patterns and IA.

Design Process & Scrum Team

UX Goals

After the design research, two major UX goals I want to achieve from the UX enhancement design: 1.Reduce UI and workflow complexity. 2.Increase the product's self-learnability.

Ideation Sketching

I like exploring design solutions by ideation sketching, using pen-and-paper sketching and whiteboarding to quickly visualize different possibilities.

❮ ❯

1.Streamline Workflows & UI

In order to simplify the complexity of interactions, I redistributed the UI controls based on product's personas, and made different UI panels on-demand.

2.Reskin UI to Reduce Visual Complexity

I explored different visual themes in order to reduce the UI complexity of data visualization.

❮ ❯

3.Enhance Affordance & Visual Feedback

In order to increase self-learnability and provide scaffolding to novice users, I enhanced the affordance of the UI, and visual feedback from interactions.

4.Provide On-board Education & In-App Help

Last but not least, I created the data visualization recipe infographic, chart templates, provided contextual in-app helps for scaffolding.

Final Deliverable

I provided the design deliverables to my front-end engineers, and played the role as an UX QA to help verify the implementations at the end. All of our UX goals were met.

1.Data Visualization with Builder & Filter Panels