Tableau Catalog
I was the UX lead for Tableau Catalog, focusing on critical business areas: data discovery, trust, impact analysis, and governance.
Tableau Catalog serves as a unique analytics catalog that bridges enterprise data management with Tableau's analytics platform, providing contextual metadata for data consumption and insights. This distinctive positioning requires designing experiences that serve diverse user needs across the data spectrum—from data administrators and engineers to analysts and business stakeholders.
In this role, I focused on uncovering complex user challenges through research and iterative design, delivering solutions that balanced user needs, business objectives, and technical constraints to drive measurable improvements in data discoverability and trust.
Data Lineage
Data lineage is a core function of Tableau Catalog, enabling impact analysis across Tableau content and external databases indexed within the Tableau environment.
After inheriting the MVP-scope UX design, I enhanced the lineage filtering experience by introducing improved visual hierarchy and clarity. I validated these improvements through multiple rounds of internal user testing, resulting in more intuitive navigation and better user comprehension of data dependencies.
To expand lineage functionality and support broader impact analysis use cases, I designed UX concepts for multi-filtering capabilities, downstream calculation visibility, and external ETL integration—all built upon the existing lineage UI framework for consistency and scalability.
Multi-filtering on lineage
Downstream calculations on lineage
External ETLs on lineage
Trust Indicators
Establishing data trust is fundamental to Tableau Catalog's mission. I focused on making data certifications and quality warnings more visible and actionable for users evaluating data reliability.
I redesigned the MVP trust indicator experience, unifying how certifications and quality warnings appear across the platform. I collaborated with the Tableau Design System team to create standardized components, establishing consistent content labeling patterns platform-wide.
Building on this foundation, I worked with product partner to extend the strategic vision for data labeling, introducing critical metadata like sensitivity and compliance indicators to help users make informed, confident decisions about their data assets.
Data Discovery
Search and filtering capabilities in Tableau Server and Cloud were significantly under-developed, resulting in poor user adoption and data discovery challenges.
To understand which metadata elements are most valuable for data discovery, I conducted internal research with data analysts. Armed with these insights, I collaborated with the Search UX team to leverage their new search patterns and create a unified data search experience across Tableau Server, Cloud, and Catalog environments.
The new search experience prioritizes relevant metadata in filters, sorting, and results to accelerate data discovery and increase user confidence. We eliminated the legacy framework that required users to select content categories before viewing results. Instead, the system now returns mixed content types ranked by relevance to the search query, creating a more intuitive and efficient discovery process.