UI considerations for designing large data tables

Data powers our world but the user interface often gets in the way. Learn design techniques to build better data tables.

Andrew Coyle
3 min readNov 10


The modern world runs on large datasets but users often suffer with poor table designs. This article explores ways to improve table UX through a number to UI considerations. Keep in mind these are just examples. The user and use case should drive your design decisions.

Arrange columns in order of importance and visually distinguish identifying columns

In this hypothetical example, the user identified the customer name as the identifying field. Positioning it as the first column and bolding the text allows the user to quickly identify and action an invoice. Also, the amount and balance due were contextually important fields to the users. Positioning them next to each other and aligning them to the right helps the user scan this information.

Fix contextual identifying column(s)

In this example, the horizontal screen space is smaller than the data in the table. Allowing horizontal scrolling and fixing the contextual identifying columns (customer name, amount, and balance due) helps the user parse the data without losing their place.

Fix column headings

Fixing column headings allows the user to scroll many rows without losing the context of the column category.

Allowing for reordering and turning columns on and off

Providing the user the ability to show and hide different fields reduces complexity when comparing, finding, and actioning data. Learn more about column customization in my recent article.

Consider reducing display density

Designers often increase whitespace to create a better looking visual design but this can get in the way of usability when managing large datasets. Consider reducing display density or give the user the option to customize table row height.

Filter searching

Adding the ability to narrow down results with a search input that filters data in real-time based on what the user types helps the user find specific items in large datasets. This can be done on a column or table basis.

Basic filter selectors

Allowing the user to select what they want to see from a predefined list allows them to quickly narrow rows to find relevant data. I plan to write more on filtering techniques and usability considerations in future articles. Stay tuned!

I aim to design, code, and write about UI components and patterns for enterprise SaaS. I’m creating a product that allows software designers and engineers to plug into a comprehensive set of UI components to build amazing interfaces. Stay tuned!

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Andrew Coyle

Formerly @Flexport @Google @Intuit @HeyHealthcare (YC S19)