Redefining Enterprise Data Discovery
Product
Enterprise platform ecosystem
4 weeks
Timeline
Methods
Exploratory Interviews
Context
As the platform expanded into a more complex Cloud Data Platform ecosystem, the team explored how to support in-platform data discovery.
Users were assumed to navigate across multiple systems (Cloud Data Platforms & Data Analysis Platforms), creating fragmented workflows, but this behavior had not been validated.
The core challenge: how do we reduce platform switching and create a cohesive discovery experience within our Enterpise ecosystem?
Research Goals
- Map cross-platform discovery workflows
- Evaluate enterprise discovery concepts
- Understand use of metadata
- Reduce workflow fragmentation
My Role
Led end-to-end research across a cross-product problem space
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Designed research approach, discussion guide, and recruitment strategy
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Tested prototype (Figma) – supplied feedback to designer
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Moderated sessions
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Conducted analysis, synthesis, and final report creation
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Aligned stakeholders on ecosystem-level questions
Impact
- Validated investment in integrated discovery
- Informed designs emphasizing contextual metadata
- Reduced reliance on cross-platform workflows
Follow-up: Prompted research on data connection ownership
Reflection
A gap in scope surfaced after the study completed around how users set up and manage data connections. Rather than reopening the study, I identified an opportunity to incorporate these questions into an upcoming cross-product research effort.
This experience reinforced the importance of early alignment with adjacent teams and flexibility when new questions emerge.
Takeaway: Research shouldn’t live in silos - strong alignment early on makes it easier to adapt later.