Data Cloud B2B SaaS Platform
Overview
The Data Cloud Configuration Platform was built to address the growing complexity of enterprise data management. Our customer needed a unified solution to manage data pipelines, configure workflows, and monitor system performance across multiple environments.
Business Goal
Increase implementation team productivity by:
I redesigned the experience into a unified, intelligent workflow orchestrator that directly addresses user needs for seamless data model mapping and ETL process configuration. The solution introduced clear action pathways, contextual guidance, and real-time validation that transformed complex workflows into an intuitive experience.
Problems Overview
The Data Cloud Configuration system faced comprehensive usability challenges across multiple critical areas that severely impacted user productivity:
Navigation Issues: Services were divided across separated interfaces creating fragmented workflows with a non-seamless experience that made scenario navigation difficult and caused constant journey disruption preventing task completion.
Design System Limitations: The outdated design system lacked modern standards and had no coverage for complex enterprise use cases, providing inadequate interface patterns for sophisticated data management needs.
System Transparency Problems: Users struggled to understand how to effectively use Data Cloud and had difficulty comprehending current configuration states due to a lack of clear system feedback and guidance.
User Pain Points: Widespread user frustration affected all user types, creating significant decision-making delays that hindered business operations and reduced productivity due to interface complexity.
Value Proposition Deficiencies: Outdated UX patterns provided no meaningful improvements and offered no enhanced functionality over users' previous workflows, presenting a modernized interface without delivering efficiency gains where the transition effort was not justified by user benefits.
These interconnected issues created a system that not only failed to meet user expectations but actively hindered their ability to perform critical data integration tasks efficiently.
The Data Cloud Configuration project tackled critical workflow inefficiencies affecting data integration specialists at Blue Yonder. These professionals, who manage complex customer data integrations across multiple systems (SAP, Oracle, IBM), were struggling with fragmented navigation, outdated design patterns, and unclear system states that made their daily tasks time-consuming and frustrating.
I conducted in-depth interviews with Blue Yonder IT Administrators and Customer IT Admins, using these insights to understand their current pain points with fragmented workflows and decision-making delays. Following the initial research, I facilitated usability testing sessions with data integration specialists to validate our unified workflow orchestrator design, which directly informed key improvements such as the contextual guidance system and real-time validation feedback that ultimately contributed to the 65% reduction in configuration time.
These research activities were essential in transforming abstract user frustrations into specific, actionable design requirements that addressed both the technical complexity of enterprise data management and the human need for clear, intuitive workflows.
Current Data Cloud Configuration User Journey (Before Redesign)
This user journey represents the existing fragmented workflow that highlights the core problems users face with the current Data Cloud Configuration system. The journey demonstrates the complex, disjointed process that contributed to the 65% inefficiency we aimed to solve.
Configuration Phase Complexity: The current journey shows five separate configuration tracks running in parallel: Data Model Management (orange), System Configuration (purple), Data Validations (blue), Data Functions (green), and Data Pipeline Management (pink). Users must navigate between these disconnected services, each requiring separate "Export to ALM" actions, creating multiple exit points and workflow interruptions. This fragmented approach forces users to context-switch constantly, with no clear sequence or guidance on dependencies between different configuration steps.
Testing Phase Isolation: The Testing Phase appears disconnected from the configuration work, requiring users to manually transition between configuration and testing without clear handoffs or state preservation. This separation contributes to the decision-making delays and user frustration identified in our problem analysis.
Key Pain Points Illustrated: This journey visualization clearly shows the navigation issues we identified - divided services, non-seamless workflows, and difficult task completion without journey disruption. The multiple parallel tracks and repeated "Export to ALM" actions demonstrate the outdated UX patterns that provided no added value compared to users' previous workflows. This complex, overwhelming interface exemplifies why users struggled to understand how to use Data Cloud effectively and why the system state remained challenging to comprehend.
This existing journey served as the foundation for our redesign efforts to create a unified, intelligent workflow orchestrator.
Creating Home Page
A unified dashboard with clear action pathways, prioritized tasks, and contextual guidance - transforming complex data management into an intuitive, efficient user experience.
Key improvements:
- Unified dashboard replacing fragmented navigation with clear priority sections,
- Action-oriented layout with prominent "Data Actions" workflow cards,
- Visual hierarchy using organized sections and improved information architecture,
- Contextual guidance through "Configuration Top Priorities" and "Services You Can Use"
- Reduced cognitive load by consolidating 8+ separate configuration areas into logical, sequential workflows.
Managing Pipelines
Looking at this Data Pipeline Management before/after comparison, here's a description text:Transformed the data pipeline experience from a cluttered, table-based interface into an intuitive visual workflow builder. The redesigned system replaces overwhelming lists and complex navigation with a clean, drag-and-drop pipeline canvas that makes data flow relationships immediately clear and actionable.
Key improvements:
- Visual workflow representation replacing dense tabular data viewsIntuitive drag-and-drop interface for building and modifying pipelines
- Clear data flow visualization showing source-to-target relationshipsSimplified pipeline creation with contextual add source functionality
- Conversational AI assistance for guided pipeline setup and troubleshooting
- Clean, focused workspace eliminating information overload
- This evolution transforms complex data pipeline management from a technical hurdle into an accessible, visual workflow that both technical and business users can understand and operate effectively.
Data Functions Management Interface
The Data Functions interface provides a comprehensive solution for managing complex data transformation workflows within the Data Cloud Configuration system, addressing critical needs for developers and data integration specialists working at enterprise scale.
Version Management System:The left panel features robust version control displaying chronological versions with clear timestamps and contributor information. The current version is prominently highlighted while previous iterations remain accessible for comparison and rollback capabilities, providing complete transparency into function evolution.
Status Tracking Dashboard:The central interface displays 246 data functions organized by workflow stages: In Progress, Code Review, Ready to Publish, and Published. Each function shows critical metadata including creator, current status, and available actions. Color-coded status indicators (Draft, Validation Success, Validation Failed) provide immediate visual feedback about system states.
Integrated Development Environment:The bottom section combines a SQL code editor with an interactive code review panel, enabling seamless developer collaboration. The review log tracks all feedback and approvals with timestamps, creating an audit trail for enterprise compliance requirements.
Key Design Improvements:This unified interface eliminates fragmented navigation by consolidating version management, status tracking, code editing, and collaboration tools into a single workspace. Clear information hierarchy and contextual organization enable users to complete complex data function management tasks without workflow disruption, directly addressing the core problems identified in the original system.
New Design System Implementation
As part of the Data Cloud Configuration redesign, I contributed to Blue Yonder's broader design system transformation initiative. This work directly addressed the outdated design system limitations identified in our problem analysis, where inadequate coverage for complex enterprise cases was hindering user productivity.
Implementation Scope: I worked across three different products with three distinct teams to ensure smooth adoption of the new Fractal Design System. This involved reviewing approximately 100 components, collaborating with Design System and Portal teams, and providing visual QA and developer training to maintain consistent implementation standards.
Key System Improvements: The Fractal Design System introduced improved "Calibre" typography for better readability, a sophisticated color system with seamless dark/light theme switching, modern icons and component styling that meet contemporary UI expectations, and a redesigned portal shell with enhanced functionality and space optimization.
Migration Results: We successfully migrated 46 components (50% of the repository) with full semantic token integration, plus 21 components with minor updates. This systematic approach utilized new semantic tokens, updated colors, and improved spacing modes throughout the interface.
Outcome: Data Cloud Configuration, along with two other products, adopted a unified design language that is smart, beautiful, and scalable—directly addressing previous value proposition deficiencies and providing meaningful improvements over legacy workflows.
Business Impact Conclusion
The Data Cloud Configuration redesign successfully transformed a fragmented, frustrating user experience into a streamlined, intelligent workflow platform that delivers measurable business value. By addressing core navigation, design system, and usability challenges, the project achieved a 65% reduction in configuration time, 70% improvement in navigation efficiency, and 50% faster onboarding—ultimately enhancing productivity for 5,000+ global users. This comprehensive solution not only eliminated user pain points but positioned Data Cloud as a competitive advantage for Blue Yonder's enterprise clients, demonstrating how thoughtful UX design can drive both user satisfaction and business outcomes at scale.