NEXTPOINT – EDA DASHBOARD

Overview

Nextpoint’s Data Mining tool introduces Early Data Assessment (EDA) capabilities to help legal teams quickly analyze large volumes of raw data before formal review.

By leveraging machine learning and advanced filtering, EDA enables users to uncover key patterns, custodians, and data types, allowing for faster and more informed decisions at the earliest stages of eDiscovery.

Hi-Fi Mockup of the Figma Prototype used for UserTesting

Project Goals

• Design a dashboard that surfaces actionable insights in a visually accessible and intuitive format.
• Enable users to search for and create custom data slices based on metadata, file types, keywords, and other filters.
• Visualize large-scale datasets (10TB+ per day) while maintaining clarity, performance, and responsiveness.
• Serve as the first layer of analysis before data enters formal import and document review workflows.

My Role

I led UX design for the Early Data Assessment experience, working closely with product, engineering, and data science teams to translate complex data signals into actionable, user-facing insights.

Methodologies & Responsibilities

• Conducted industry research and persona development to understand common EDA workflows in legal technology.
• Designed low- to high-fidelity prototypes visualizing custodian trends, file type distributions, and query-based results.
• Created flexible search interaction patterns allowing users to explore datasets through filters, keyword logic, and metadata attributes.
• Partnered with data science to align machine learning outputs with usable UI components, including transcription views and signal highlights.
• Produced detailed design documentation, logic diagrams, and annotated specs to support engineering handoff.

Key Features Designed

• Interactive dashboard with real-time charts and tables for custodians, file types, date ranges, and keyword hotspots.
• Search-driven exploration tools, including modular filters and query builders for narrowing large datasets.
• Machine learning integrations to surface extracted text, language classification, and media detection insights.
• Slice creation workflows for selecting, saving, and exporting custom data subsets for review.
• Accessibility- and scalability-focused design supporting WCAG standards and high-volume data environments.

Impact

This product was iterated on after my departure and was successfully launched in January 2026, building on the foundational UX patterns, workflows, and design system established during the initial design phase.

Tools

Design & Research

Figma, Sketch, Zeplin, UserTesting.com, Mural

Communication

Slack, Zoom, Jira, Confluence