Characters & Roles
YellowLine NYC engagement — MHP consulting team
Use these names consistently in animations, modules, and trainer narration.
| Character | Role | Narrative function |
|---|---|---|
| Marcus Chen | Operations Manager, YellowLine NYC | Client sponsor; states business pain and constraints |
| Elena Vasquez | Data Architect, MHP | Designs medallion architecture; leads tool evaluation |
| Bob Müller | Junior Data Engineer, MHP | Hands-on builder; trainee proxy |
| Sofia Alvarez | Senior Data Engineer, MHP | Mentors Bob on Databricks / PySpark |
| Priya Sharma | BI Analyst, MHP | Defines KPIs; builds Power BI dashboard in the story |
| James Okonkwo | Data Analyst, MHP | Validates KPI logic with SQL |
Character Details
Marcus Chen — Operations Manager at YellowLine NYC. Runs a fleet of 400+ yellow taxis in Manhattan. Frustrated by spreadsheets that break and dashboards that lag behind reality. His three non-negotiable constraints: cost (TCO must be justifiable to the board), performance (dispatch needs near-real-time visibility), and compliance (audit-proof numbers for Q3 regulatory review). He doesn’t care about technology — he cares about outcomes.
Elena Vasquez — Lead Data Architect at MHP. 12 years of experience across banking, logistics, and mobility. Designed the medallion architecture that all three pipelines follow. Vendor-neutral by principle — she evaluates tools on merit, not marketing. Her closing line in Module 7: “Technology is a decision. Architecture is responsibility.” She approves all tool pivots; Bob never “picks vendors” alone.
Bob Müller — Junior Data Engineer at MHP, 2 years out of university. The trainee proxy — when trainees build pipelines, they are Bob. He asks the questions trainees are thinking but might not voice. Elena mentors him through architecture decisions; Sofia guides him through Databricks specifics.
Sofia Alvarez — Senior Data Engineer at MHP. Databricks specialist who guides Bob through PySpark, Delta Lake, and cluster management. Appears in Modules 0, 2–3, 8–9 — mentoring Bob in Databricks (Module 2), porting Silver rules to Snowflake (Module 3), and streaming / ML labs (Modules 8–9).
Priya Sharma — BI Analyst at MHP. Defines the 12 KPIs that all three pipelines must produce identically. Builds the Power BI dashboard in the story. Her Gold schema is the contract — same tables, same columns, regardless of which pipeline engine produced them. Speaks in Modules 0–4, 6–9 (every module except Module 5).
James Okonkwo — Data Analyst at MHP. Validates KPI logic by writing independent SQL checks against Gold tables. Ensures the numbers Priya’s dashboard shows match the source data. Appears in Modules 0–1, 4, 6, 8–9.
Think & Discuss
Situation: YellowLine NYC has millions of taxi trips but no analytics platform. Marcus hired MHP. Priya needs KPIs; Elena wants medallion architecture — nothing is built yet.
Prompts:
- What is Marcus’s biggest problem in your own words?
- If you split data into layers, how many would you use and what goes in each?
- Priya needs a dashboard — what must exist before she can build it?
Capture 3–5 bullets on the whiteboard. Do not reveal answers yet — theory and labs validate trainee ideas.
Trainee instruction
Today you are Bob. Elena designed the architecture; your job is to build, evaluate, and recommend tools for Marcus.
Role boundaries (credibility)
- Elena approves tool pivots (Databricks → Snowflake → dbt) — Bob does not “pick vendors” alone.
- dbt is always framed as a transform layer on Snowflake, not a warehouse replacement.
- Priya consumes Gold KPI tables in Power BI — same schema regardless of pipeline engine.