Anonymized engagement summary: Power BI architecture, data model and operational dashboard for a public transit district (2023)
Contracted — countersigned (EPC-reported; documents private)First-pass editionA public transit district (client not named) · 2023 · Project ID EPC-2023-ANON-TRANSIT-PBI
Last updated by Errin O'Connor, Founder & Chief AI Architect, EPC Group
Opening answer. In July 2023 a public transit district's General Manager countersigned a statement of work with EPC Group to optimize its existing Power BI reports and dashboards. The scope:
- a Power BI architecture built around end-user requirements and business goals
- connections to the district's source data systems
- a best-practice data model for analysis and reporting
- custom reports and an operational dashboard on established business metrics and KPIs
- training and knowledge transfer so the district's technical staff can run the platform themselves
Disclosure. This is an EPC-reported anonymized engagement summary. The client is not named. The countersigned statement of work is retained privately and is not published in the Evidence Center, so this account is outside the Evidence Center's documented-engagement counts. Every engagement fact below is taken from that document.
Verification class
Contracted — countersigned (EPC-reported; documents private). The district's General Manager signed the statement of work in July 2023. No acceptance record, dashboard inventory or outcome measurement is cited or claimed.
Buyer problem and scope
| Item | What the statement of work states |
|---|---|
| Buyer | A public transit district (client not named); signed by its General Manager |
| Situation | Existing Power BI reports and dashboards that the district wanted to optimize |
| Support and architecture | A Power BI architecture centred on end-user requirements, business goals and best practice; provisioned to integrate with the district's source data systems; all data sources connected and routed correctly; a best-practice data architecture model for loading data into Power BI for predictive analysis and reporting |
| Reports and dashboards | Custom reports and dashboards on existing datasets and on specific KPIs and metrics, an operational dashboard, and further customizations as needed |
| Knowledge transfer | Training so the technical staff know the features, functions and best practices well enough to manage the platform |
| Work areas | Assessment and discovery; design and development; source data integration; reports and the operational dashboard; quality assurance and testing; rollout; post-deployment support; on-the-job knowledge transfer |
Unknowns, not stated in the document cited: the source systems involved, the dashboard's specific measures, user counts and any measured result.
Approach and artifacts
Start from what each department wants to measure. The assessment phase covers several things before any build:
- gathering stakeholders' reporting expectations
- identifying the types of Power BI consumers
- naming the key metrics each team and department wants to track
- reviewing the source systems, including how data is prepared and extracted
- a gap and fit analysis with remediation recommendations
Architecture before visuals. The data model and source connections are designed first, then the operational dashboard and the KPI reports are built on them.
Leave the district self-sufficient. EPC Group's developers work side by side with the district's technical staff throughout, so knowledge transfer happens on the job as well as in training.
Document (held privately):
| Document | Date |
|---|---|
| Statement of work, Power BI consulting and development (countersigned) | July 2023 |
Results and limitations
| Claim | Basis | Status |
|---|---|---|
| The district contracted EPC Group to optimize its Power BI estate and build an operational dashboard | Countersigned statement of work, July 2023 | Contracted (EPC-reported; documents private) |
| Dashboards delivered, accepted or in use; any measured result | No document cited | Not claimed |
Provenance
- Source: the countersigned statement of work (July 2023), held privately. Engagement ID: EPC-2023-ANON-TRANSIT-PBI, an alias unrelated to the client's name.
- Anonymization: sector and organization type only, under EPC Group's anonymized-case rule; the district's name, location, staff names and commercial terms are not published.
- Not claimed: client endorsement, delivery, or any measured result.
- Author: Errin O'Connor, Founder & Chief AI Architect, EPC Group, named in the statement of work as leading the initiative.
Revision history
- 2026-10-25: anonymized engagement summary published from the engagement's countersigned statement of work.
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Author: Errin O'Connor, Founder & Chief AI Architect, EPC Group · Published: 2026-10-25.