A federal transportation agency operated six independent IT systems with no unified view of spend, program status, or resource utilization. We built a Power BI reporting layer on Azure Government with row-level security by bureau and automated FITARA scorecards, eliminating manual quarterly consolidation and providing real-time compliance transparency.
The agency managed IT infrastructure across multiple bureaus, with each bureau operating its own systems for asset management, spend tracking, and program status. While individual systems were functional, the agency had no enterprise view of IT portfolio health, making FITARA compliance reporting a manual, quarterly exercise that required weeks of spreadsheet consolidation.
Leadership needed defensible, real-time data on IT spending, project status, and resource allocation to meet federal modernization mandates. The solution had to operate inside FedRAMP boundaries and provide role-based access control by bureau to protect sensitive information.
We mapped all six source systems, built Python ETL pipelines in Azure Government, deployed Power BI Premium with row-level security by bureau and role, then automated the FITARA scorecard and trained the agency's analytics team on self-service publishing.
FITARA scorecard, spend by bureau, project portfolio, resource utilization, and trend analysis. All dashboards accessible to authorized users within 24 hours of policy.
Quarterly manual consolidation reduced to real-time automated dashboards. Leadership now monitors compliance continuously instead of quarterly snapshots.
All infrastructure, data flows, and RLS logic built within Azure Government boundaries. Passed agency compliance review with audit trail intact.
FedRAMP-compliant cloud infrastructure, hosting all data pipelines, databases, and Power BI workspaces within the boundary.
Orchestration platform for automated ETL pipelines connecting six source systems with error handling and audit logging for compliance.
Enterprise BI platform with row-level security by bureau and role, semantic modeling, and dedicated capacity for live dashboards.
Data transformation logic and dimensional warehouse hosting semantic layer, supporting real-time Power BI connections and audit requirements.
Bring the problem. We'll come back with a written brief, what to build, what to defer, and where AI actually moves the number. No deck pitches.