Improving the UX of Data Tables

Ongoing

Industry: Enterprise software

This initiative aims to enhance the UX of data tables in an enterprise setting by optimizing layouts, improving sorting and filtering, and ensuring better mobile responsiveness.

Role

UX/UI designer

Paired with

Design team, Design systems lead

Platform

Web responsive

Data tables are essential for presenting structured information in enterprise software, yet they often create friction for users trying to find, analyze, and act on data efficiently. In many cases, this stems from overlooked usability gaps—and I’ve made it my mission to identify and document these pain points, using those insights to guide improvements that simplify interaction and support better decision-making.

01 The problem

Through user testing, feedback, and design audits, common usability issues in data tables began to emerge—slowing users down and increasing cognitive load.
Many of these issues stemmed from fragmented patterns and outdated components that lacked consistency across products.
Rather than continuing with one-off fixes, I saw the need for a scalable approach—shifting the focus toward a unified framework for data table UX grounded in research and long-term usability.

02 Research

My research focused on how companies structure data-heavy tables across both large and small screens. I looked at how different layouts handled density and interaction, and how default states impacted usability—ensuring that key information remained visible and actionable without overwhelming users. Performance and responsiveness were also key factors in evaluating how these patterns held up across platforms.

03 Ideation

During the ideation phase, I focused on categorizing the different data table experiences by function and use case, creating a framework that would allow for consistent and intuitive user interactions.

Introduced a new design taxonomy to distinguish between action- and information-oriented tables, unlocking reusable design logic across the platform.
Proposed an adaptive filtering model, now being explored as a design system pattern for other data-heavy modules.
Advocated for a componentized, cross-functional approach to designing with engineering, influencing how future tables are built org-wide.

04 Testing

As part of the iterative design process, I am exploring various ideas to improve the usability and efficiency of data tables. While some approaches show promise, others have revealed challenges during testing, providing valuable insights:

Overly complex filtering options:
Initial testing showed that advanced filters overwhelmed users with basic needs, prompting a shift toward simpler defaults with optional advanced controls.
Dense data on small screens:
Compact layouts improved information density but hurt readability and usability in testing, leading to a shift toward more legible, touch-friendly mobile designs.
Confusing inline actions:
Users struggled to interpret in-row actions during testing, prompting exploration of clearer labels and visual cues to improve understanding.

These ongoing tests and insights are shaping the next phase of design iterations. By addressing these challenges, I aim to deliver a solution that balances functionality, clarity, and ease of use while meeting user needs.

05 Learnings

In enterprise environments with significant design and tech debt, I prioritize defining high-level standards before making changes. This ensures updates are aligned with best practices and lay a scalable foundation for consistent, user-centered improvements.