Business Intelligence (BI) Platform

Analytics Hub

A business analytics solution designed to help enterprise leaders monitor performance, improve efficiency, and make informed decisions. The platform provides real-time insights, dashboards, and data visualizations tailored to different user roles.

Collaboration Overview

Role

UX Designer

Duration

12 months

UX Team

1 Lead UX Designer, 2 UX Designers

Collaborators

Product Manager, Business Stakeholders, Development Team

Problem

The existing analytics system failed to deliver a cohesive and insightful experience, making it challenging for users to manage, interpret, and share business data effectively.

Lack of Unified Reporting Flow

Users are forced to switch between multiple tools, creating a fragmented and inefficient reporting experience.

Weak Data Visualization

Cluttered and inconsistent visual representations prevent users from easily identifying trends, patterns, and performance gaps.

Scattered Data Sources

Disconnected datasets make data management complex, reducing trust and making it nearly impossible to maintain accuracy.

Heavy Manual Dependency

Frequent manual updates and repetitive data uploads make the workflow slow, error-prone, and difficult to maintain.

Business Goals

Transform complex data into clear, actionable insights
Increase user trust and platform credibility
Ensure data privacy and regulatory compliance
Enable role-based, controlled data access
Strengthen decision-making confidence across teams

Project Brief

The Analytics Hub redesign aimed to transform a fragmented, data-heavy system into a unified, user-centric analytics platform. During Empathy & Discovery, the team conducted competitive analysis, 8+ user interviews, and contextual research to understand how users interact with data, what KPIs they need, and where current workflows break. Key insights revealed the need for a centralized dashboard, automated data integration, clearer navigation, drill-down capabilities, and role-based access. In the Define & Ideate phase, the team translated research into personas (consumer, uploader, downloader, admin), mapped insights through affinity diagrams, prioritized features using an impact-effort matrix, and designed user flows and information architecture to clarify data movement and user journeys. During Design Iteration & Prototyping, they created low-fidelity wireframes, explored data visualization patterns (cards, graphs, tables), and developed high-fidelity screens with consistent UI, secure user-based login, tile-based dashboards, improved charts, and clear download/reporting options. These iterations focused on reducing cognitive load and enabling fast, insight-driven decision-making. Overall, the redesign turned a complex reporting system into an intuitive, role-aware analytics tool that supports clarity, efficiency, and better business decisions.