DEX Trading Infrastructure Dashboard
Design of a real-time trading and liquidity analytics dashboard for decentralized exchanges, translating complex blockchain data into actionable insights for traders and analysts.
Context & Problem
Decentralized exchanges like Uniswap operate on blockchain infrastructure where liquidity, pricing, and execution data are fragmented and highly technical. Through research and stakeholder collaboration, a key behavioral insight emerged: traders don’t explore interfaces, they scan for signals. Existing tools required switching between multiple platforms, increasing cognitive load and slowing down decision-making in time-sensitive environments.
↓ 30–40%
faster time to insight after dashboard adoption
High
cognitive load due to fragmented data
3–5 tools
required in previous workflows
My Role
Contributed to the design of a trading analytics dashboard, focusing on solving complex data interpretation challenges and establishing scalable foundations through a reusable design system.
- Translated complex blockchain and trading data into scannable UI patterns
- Helped define key product challenges around data clarity and decision-making speed
- Contributed to a modular design system to ensure consistency and scalability
- Collaborated with engineering and data teams to align design decisions with technical constraints
Project Gallery
Process
Discovery
- Mapped key trading metrics (liquidity, volume, slippage, execution)
- Collaborated with domain experts to understand DEX mechanics
- Identified a core insight: traders prioritize speed and signal detection over deep exploration
Definition
- Prioritized core needs: scanability, comparability, and real-time feedback
- Defined a clear data hierarchy to surface high-signal metrics by default
- Made intentional trade-offs by limiting visible data to reduce noise and cognitive load
Design
- Designed high-density dashboards optimized for rapid visual parsing
- Created reusable components for consistent data representation
- Balanced flexibility vs clarity by constraining customization in early iterations
Validation
- Tested layouts with traders to validate scanning behavior
- Iterated on hierarchy to reduce time to key insights
- Refined data grouping to better match user mental models
Design Principles
Design for scanning, not reading
Users need to detect patterns and signals in seconds.
Clarity requires subtraction
Removing non-critical data is essential to reduce cognitive load.
Consistency builds trust
Standardized data patterns reduce interpretation errors in high-stakes decisions.
Results / Impact
The dashboard helped transform fragmented workflows into a more unified decision-making experience, improving both speed and confidence when interacting with DEX data.
- Reduced time to identify key trading signals by ~35%
- Decreased reliance on multiple tools by consolidating workflows into a single interface
- Improved decision confidence through clearer and more consistent data visualization
Reflection & Learnings
- —In complex domains, what you choose to hide is as important as what you show
- —User behavior (scan vs read) should directly shape layout and hierarchy decisions
- —Design systems are critical for scaling data-heavy products consistently
Tools & Methods
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