GEM has been providing reinsurance to public entity risk pools for over 20 years. During that time, claims administration has relied on a third-party administrator, with reports either generated by the TPA or assembled manually by your 10-person team.
That approach worked when the data was simple. It doesn't scale. Here are the four constraints holding GEM back:
Loss runs come once a month. You can't do point-in-time reporting, and current-month exposure is invisible until the next cycle.
Every analytical request is a manual exercise. Staff spend hours assembling reports that should take minutes.
Claims data lives in C3, financials in spreadsheets, contracts in files. No single source of truth, no cross-cutting analysis.
When aggregate deductible limits are hit or litigation is forthcoming, you find out late. There is no automated detection.
This proposal outlines a five-phase approach to solve all four: a cloud-hosted data warehouse on Azure, automated daily ETL from your TPA, interactive dashboards with real-time alerts, and full knowledge transfer so your team owns the result.
We have been building data warehouses, ETL pipelines, and reporting platforms for 15 years. Not as a side offering inside a larger IT consultancy. As our core business.
Our track record includes analytics infrastructure for Worldcoin (global fintech), claims analytics for CC Response (insurance services), and a full fractional Head of Data engagement for Sniffspot, a $6M-revenue marketplace where we built the data warehouse, KPI framework, and executive dashboards from scratch.
We are a boutique firm. Nick Valiotti, the founder, serves as Solution Architect on every engagement. You get senior-level talent from day one, not junior consultants learning on your project. Our team is small enough for direct communication, experienced enough for enterprise-grade delivery.
Every system we build is designed for handoff. Full documentation, recorded training sessions, editable scripts. The goal is GEM owning its platform, not depending on us indefinitely.
Five phases, 20 weeks. Each phase produces concrete deliverables that GEM reviews and approves before we proceed. You see working dashboards by Week 10, not Week 20.
Weeks 1–3. Requirements workshops, TPA extract mapping, data quality assessment. Complete data dictionary with business definitions. Cleansing recommendations.
Weeks 4–8. Dimensional model for claims, policies, financials, CRM, TPA activity. Database objects, scripts, and documentation—all delivered to GEM.
Weeks 6–10. Daily flat-file ingestion from C3 via Azure Data Factory. Historical data migration. Validation rules, error handling, reconciliation.
Weeks 8–14. Power BI dashboards per member. Loss runs, trend analysis, peer analysis. Automated alerts for aggregate limits, litigation, reserves.
Weeks 12–16. Hands-on sessions for GEM staff and TPA personnel. Full documentation package: architecture, integration, schema, ETL, and dashboard guides.
Weeks 16–20. Production monitoring, performance tuning, final documentation updates. Included in the implementation cost.
Azure SQL Database (or Synapse Analytics if future scale warrants). Azure Data Factory for ETL. Power BI for dashboards and ad hoc reporting. All deployed within GEM's existing Azure tenant in coordination with your MSP.
| Week | Phase | Key Milestones |
|---|---|---|
| 1–3 | Discovery | Kick-off • Requirements sign-off • Data dictionary complete |
| 4–5 | DW Design | Data model review • Schema approval |
| 6–8 | DW Build + ETL | Database deployed • ETL development begins |
| 8–10 | ETL Complete | Historical data loaded • Daily pipeline operational • Validation checkpoint |
| 8–12 | Dashboards | First dashboards live • Report library build-out |
| 12–14 | Reports + Training | Alert system live • Training sessions begin |
| 14–16 | Handoff | Knowledge transfer complete • Documentation delivered |
| 16–20 | Stabilization | Production monitoring • Performance tuning • Final sign-off |
Five people, each with a defined role. No subcontracting to unknown parties.
MS in Analytics (Georgia Tech). 15+ years in data. Led DW implementations across fintech, insurance, and marketplace companies. Involved in every phase from discovery through handoff.
5+ years at Valiotti Analytics. Manages engagements end-to-end: scheduling, stakeholder communication, milestone tracking. Your day-to-day contact.
3+ years at Valiotti Analytics. Requirements gathering, data mapping, business rule documentation. Translates GEM's needs into technical specifications. Leads UAT.
Azure Data Factory, SQL Server, flat-file ingestion, data validation. Builds the daily pipeline, handles historical migration and scheduling.
A dedicated Senior Data Analyst / BI Developer rounds out the team, responsible for Power BI dashboards, DAX, alerts, and the ad hoc reporting layer.
This covers everything: design, development, data migration, training, documentation, and one year of maintenance and support. No hidden fees.
| # | Item | Cost |
|---|---|---|
| 1 | Discovery & Data Dictionary | $12,000 |
| 2 | Data Warehouse Design & Build | $22,000 |
| 3 | ETL Development | $25,000 |
| 4 | Reporting & Dashboards | $22,000 |
| 5 | Training & Knowledge Transfer | $8,000 |
| 6 | Year 1 Maintenance & Support | $6,000 |
| Total Implemented Cost | $95,000 |
Does not include Azure infrastructure costs (compute, storage, licensing), which are borne by GEM through your existing tenant and MSP.
| Classification | Rate |
|---|---|
| Project Lead / Solution Architect | $200/hr |
| Project Manager | $100/hr |
| Business Analyst | $120/hr |
| Data Engineer | $125/hr |
| Data Analyst / BI Developer | $125/hr |
After Year 1, you choose the model that fits GEM best:
Not measured by the number of dashboards built. Measured by what changes for GEM:
Review this proposal and send any questions.
Demo call to walk through our approach.
Contract execution and NDA signing.
Kick-off within 5 business days of contract.
Questions? Reach out directly—we respond within one business day.
If awarded the engagement, Valiotti Analytics Ltd will maintain the following coverages in full force for the duration of the project:
| Coverage | Minimum Amount |
|---|---|
| Commercial General Liability | $2,000,000 per occurrence |
| Errors & Omissions | $3,000,000 per occurrence |
| Cyber Liability | $2,000,000 per occurrence |
| Workers’ Compensation | Per statutory requirements |
Evidence of coverage will be provided upon contract execution.