Designed end-to-end work flow within a short period, that would be used by multiple roles like Business Analysts, Data Stewards and Data Catalog Administrators
Conducted stakeholder interviews and discussions with data scientists, product managers, and engineers and used findings to inform design decisions
Ran user research, and testing using interactive prototype walk throughs with customers
REFlection
Learnings
Effectiveness of showing mockups to drive conversation Showing visuals was helpful while sharing my initial ideas with the cross-functional stakeholders. I could better communicate with engineers, product managers, and UX researchers about the design requirements, feasibility and timeline by showing them low fidelity concept mockups.
Importance of a well defined scenario Every industry could have different data management and governance use case scenarios therefore getting into the specifics of a scenario and being as detailed as possible helped me design more robust workflows
Designing for AI I realized designing for AI was designing for probability. The answer is never a definitive yes or no but a percentage value. Here you need an external human opinion to train the AI system. When working in this scenario many existing UX patterns like taking bulk actions don't work. Building trust with the user is of utmost importance in these systems.
All of my work during this internship is under an NDA. Feel free to reach out to me if you would like to learn more.
