HPE Ezmeral (Unified Analytics)

Project Overview

HPE Ezmeral Unified Analytics is an enterprise data platform that unifies data management, AI, and analytics in a single solution. The platform provides transparent secure access for AI workloads, analytics, and data lakes while enabling consistent data access across diverse environments.

As UX Engineering Manager, I led a cross-functional teams through the complete product development cycle. While helping the development team build a comprehensive Storybook and platform framework, I helped a team of designers through extensive user testing on application designs. We successfully built and shipped the application to customers across 11 countries in just 6 months.

Key Features

• Unified data lakehouse architecture
• Real-time data processing and analytics
• Integrated governance and compliance tools
• Multi-cloud and hybrid deployment support
• Enterprise-grade security and access controls
• Native support for AI/ML workloads

Technical Architecture

• React-based frontend with Storybook component library
• Kubernetes-native containerized architecture
• Support for multiple data formats (HDFS, S3, NFS, POSIX)
• Integration with Apache Spark, Presto, and other analytics engines
• Built-in data governance and lineage tracking
• Enterprise authentication and authorization systems

Development Challenges

The main challenges included:

• Balancing comprehensive user testing with aggressive timeline
• Building a scalable UI framework for complex data workflows
• Ensuring consistent user experience across diverse data sources
• Meeting enterprise security and compliance requirements
• Coordinating international rollout across 11 countries

Key Learnings & Impact

While we successfully delivered a robust product to global customers, the project taught us valuable lessons about market timing and testing efficiency. We spent considerable time on user testing, which, while ensuring high quality, ultimately delayed our market entry and caused us to miss some early opportunities.

However, the platform's emphasis on ease of use and comprehensive feature set has proven successful over time. The product continues to be competitive in the market today, with its unified approach to data management and analytics resonating well with enterprise customers seeking to simplify their data infrastructure.