Users struggled to find relevant data efficiently within the complex enterprise data catalog system. The existing search functionality was basic and often returned irrelevant results, making it difficult for users to discover the data they needed for their projects. The challenge was to create an intuitive search experience that could understand user intent and provide accurate, contextually relevant results while maintaining the system’s enterprise-grade security and performance requirements.
We had to think of the Advanced Search feature for medical professionals, with customizable filters for entities and keywords. We felt through research that we could safely draw out a flow for users.
I conducted extensive user research to understand search behaviors and pain points within enterprise data discovery. The design process involved analyzing existing search patterns, studying successful search implementations like Bloomberg’s terminal, and creating user journey maps for different data discovery scenarios. I developed wireframes focusing on search result clarity and implemented a predictive search system with intelligent categorization. Multiple iterations were tested with data analysts and business users to refine the search accuracy and user experience.
The client's brand colors were dark blue, green, and gray. We established a design system following branding guidelines, ensuring consistency and professionalism across all design elements to reinforce the brand identity.
We ensured users could search for direct items on the welcome page before searching for an asset, helping them to find an exact asset.
After conducting user interviews, evaluating business goals, and considering feedback, users should be able to access the Data Asset View and customize it by applying specific filters within the Data Asset Details. The advanced search feature allows users to filter entities based on user-selected criteria to find data assets by name. Several design iterations were explored before the final version was selected.
We saved the client 20% ROI by saving time, reducing errors, boosting productivity, increasing satisfaction scores, lowering labor costs, and increasing revenue.
