CASE STUDY: Building a Next-Generation Data Governance Platform for Utility Decision Support
Client Overview
Client: A major US Utility, guided by PA Consulting Group
Industry: Utility & Energy
Project: Enterprise Decision Support & Data Governance Organization (EDGE)
Objective: Develop a modern data governance and decision support platform to enhance data-driven insights, operational efficiency, and regulatory compliance.
EXECUTIVE SUMMARY
Driving Real-Time Insights & Compliance
The client faced inefficiencies due to legacy IT systems that depended on human knowledge rather than structured data. Codibly, subcontracted by PA Consulting Group, developed the EDGE Solution Platform—a state-of-the-art decision support system combining governed data processes with AI-driven analytics. By leveraging Azure, Databricks, PowerBI, and custom transformations, the client achieved real-time decision-making, improved operational efficiency, and enhanced regulatory compliance.
Challenges
• Outdated data systems built for a retiring workforce, lacking integration with modern analytics and AI solutions.
• Multiple siloed databases preventing a unified view (“Golden Record”) for enterprise decision-making.
• Growing stakeholder demands for streamlined asset management, compliance, and real-time reporting.
CHALLENGES
Obstacles in Utility Modernization
Legacy Systems
• Built for a retiring workforce, dependent on human knowledge.
• Data locked in siloed databases, hindering mission-critical insights.
Rising Expectations
• Regulators & stakeholders demand high-quality, real-time data.
• Public perception and financial performance hinge on accurate reporting.
Workforce Transformation
• Traditional processes not optimized for AI-driven insights.
• Missing unified governance structure for large-scale analytics adoption.
Compliance Gaps
• Disconnected data sources complicate reporting.
• Limited transparency for audits & regulatory checks.
SOLUTION
How Codibly Built the EDGE Solution Platform
1. EDGE Data Platform
• Consolidated disparate data sources into a centralized ‘Golden Record.’
• Advanced ETL pipelines using Azure Data Factory & Databricks for real-time processing.
2. EDGE KPI & INDICES Application
• Machine Learning-powered analytics engine to calculate KPIs & forecasting.
• PowerBI dashboards for secure, governed reporting.
3. EDGE Decision Support Applications
• AI-driven system addressing structured queries from a continuously learning knowledge base.
• Azure Synapse for large-scale data analysis and sub-second queries.
4. EDGE Interactive Information Applications
• Self-service analytics tools & ad-hoc reporting for day-to-day operational insights.
• React-based front end for intuitive, multi-user accessibility.
IMPLEMENTATION
How We Delivered the Platform
Codibly operated under PA’s strategic guidance, maintaining an agile, autonomous execution model to ensure timely and efficient outcomes.
Agile Dev & Sprints
• Iterative releases, continuous feedback
• Rapid prototyping for KPI apps & dashboards
Cloud-Native Infrastructure
• Microsoft Azure for scalability
• DevOps with CI/CD & automated testing
Self-Directing Team
• Codibly operated day-to-day under a single team ethos
• Close collaboration with client’s internal data unit
DevOps Best Practices
• Automated build & deployment pipelines
• Shift-left testing & continuous monitoring
TECHNOLOGIES & FRAMEWORKS
Tools Driving the EDGE Platform
We leveraged a modern, cloud-centric stack to ensure scalability, security, and performance across the enterprise data pipeline.
Azure & DevOps
• Azure Data Factory, Data Lake, Synapse, and Service Bus
• CI/CD pipelines & Infrastructure as Code with Azure DevOps
• Cloud-based environment for agility and security
.NET Core & Python
• Back-end data services, API integration, analytics tasks
• Python for ETL, data transformations, advanced ML prototyping
• Flexible architecture for microservices and event-driven design
Databricks & Power BI
• Large-scale data processing with Spark clusters
• Advanced analytics & ML workflows
• Real-time dashboards with interactive BI layers
Security & Compliance
• Role-based access control for data governance
• Adherence to corporate & regulatory guidelines
• Automated testing & QA with integrated pipelines
TIMELINE
Workflow and timeline
Spanning 11 months, the project progressed through iterative releases, ensuring continuous collaboration, rapid iteration, and minimal disruption to the client’s daily operations.
Month 1–2
- Setup & Planning: Project Manager and Dev Lead configure JIRA/Confluence, finalize architecture outline.
- Sprint Kickoff: Begin initial sprints to define key features and design data models.
Month 3–4
- ETL Implementation: Data Engineers integrate & transform 70+ datasets.
- Early QA & UI Prototypes: QA Engineer tests data flows, front-end prototypes developed for KPI dashboards.
Month 5–8
- Advanced ML & Data Governance: Additional Analysis Logic and ETL enhancements refine KPI models.
- Governance Pilot: Testing data stewardship, security roles, and compliance frameworks.
Month 9–11
- Full-Scale Deployment: System rolled out enterprise-wide with robust acceptance testing.
- Training & Handover: Knowledge transfer to internal staff, finalizing documentation for long-term sustainability.
SOFTWARE APPROACH
Agile, Collaborative, and Incremental
Our delivery methodology combined agile rituals (daily standups, sprints, retrospectives) with a strong emphasis on knowledge sharing. This ensured flexible response to changing requirements and effective collaboration across globally distributed teams.
One-Team Mindset
• Unified PA–Codibly scrum teams
• Daily checks on blockers, continuous feedback loops
• Transparent tracking in JIRA & Confluence
Incremental Releases
• Frequent sprints delivering partial yet valuable features
• Continuous user feedback & acceptance testing
• Early detection of design or data integration issues
Knowledge Transfer
• Co-located knowledge sessions with the new CDO office
• Documented best practices & data governance guidelines
• Onboarding internal staff to sustain the platform post-project
Value Delivery
• Prioritized features that offered direct business impact
• Balanced technical excellence with quick wins
• Enhanced ROI with each incremental build
RESULTS & FINAL OUTCOMES
A Data-Centric Future for Utility Efficiency
- Data Availability & Governance: Reduced data silos and boosted data accuracy by 80%, leveraging AI-driven analytics for real-time insights.
- Faster Decision-Making: Decreased manual data processing by 60%; standardized reporting significantly improved compliance and transparency.
- Operational Efficiency & Cost Savings: Automated workflows cut overhead by 40%; intuitive dashboards consolidated multiple reports into a single pane of glass.
- Single Curated Platform: Eliminated redundant databases with a governed data environment, enhancing reliability and stakeholder trust.
- ML-Driven Insights: Enabled advanced forecasting and asset management decisions through high-performance analytics.
- Reduced Time-to-Report: KPI/Indices and ad hoc queries slashed reporting cycles from weeks to hours.
- Knowledge Retention: Transitioned away from a “vanishing workforce” dynamic via documented logic and self-service dashboards.
These outcomes positioned the client to address rising regulatory demands and improve public perception by providing transparent, high-quality data. Codibly’s agile approach ensured alignment with PA’s broader strategic vision, culminating in a robust data platform ready for future expansions.
Client testimonial
What Our Partners Say
Codibly’s team brought not just technical expertise but a collaborative approach that was crucial in navigating the complexities of this project. Their ability to integrate seamlessly with our team, adapt to evolving requirements, and consistently deliver high-quality solutions under tight timelines was impressive. Codibly’s commitment to excellence and their deep understanding of the utility sector contributed to the project’s success, enabling us to achieve our goal of transforming our client’s data management and decision support capabilities.
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