USC, Annenberg School of Journalism & Communication
Annenberg Operations Analytics
Snowflake pipelines and a data-vault schema behind equipment and A/V operations.
May 2023 – May 2024
Framed for
Snowflake pipelines and a data-vault model over messy operational sources
Built the pipelines, the data-vault schema, and the automated Power BI and Streamlit reporting layer, plus prescriptive ML for staffing optimization.
- Data Vault
- schema over unstable sources
- Automated
- Power BI + Streamlit reporting
- ↓ downtime
- A/V and network
- Snowflake
- Data Vault
- Power BI
- Streamlit
- Prescriptive ML
Weekly stakeholder reviews turning operational pain into a data model
Owned the analysis, the architecture, and the stakeholder relationship, leading weekly reviews while reducing overdue-equipment incidents and A/V downtime.
- Weekly
- stakeholder review cadence
- ↓ response time
- staffing + CRM workflows
- ↓ incidents
- equipment overdue
- Stakeholder Management
- Data Modeling
- Snowflake
- Server Administration
The problem
Equipment was going overdue and A/V and network downtime was going unmanaged, because the operational data lived in disconnected systems with no shared model and no automated reporting.
What I built
- 01Built Snowflake pipelines and a data-vault schema to give the operational data a single, auditable model.
- 02Automated Power BI and Streamlit dashboards on top so reporting stopped being a manual task.
- 03Developed prescriptive ML models for staffing optimization.
- 04Streamlined staffing and CRM workflows to cut response times.
- 05Led weekly stakeholder reviews and managed server administration with a security focus.
Outcome
Reduced equipment-overdue incidents and A/V and network downtime, and cut response times through streamlined staffing and CRM workflows.