We built a mock Enterprise Data Warehouse Dashboard using synthetic data created with generative AI to practice real-world informatics skills. Through this project, we learned how to map data sources, design an ETL workflow, create a star schema, address data quality issues, and translate complex information into a clear, usable dashboard.

Competencies developed:
3.1k – Analyze primary and secondary population health data for multiple populations against relevant benchmarks.
5.1i / 5.1k – Establish and incorporate data driven benchmarks to monitor system performance; integrate outcome metrics to inform change and policy recommendations.
8.1i – Propose a plan to influence the selection and implementation of new information and communication technologies.
8.2f – Generate information and knowledge from health information technology databases.

Explanation:
This assignment is really about building the data infrastructure that turns raw health data into something usable, so most of it lands in the informatics domain. Setting up the ETL process and star schema shows the ability to pull knowledge out of health databases (8.2f), and designing the source systems map and pipeline shows input into choosing and setting up new health technology (8.1i). The KPI table with targets and data stewards shows setting benchmarks and using outcome data to guide decisions (5.1i/5.1k). And comparing rates like flu vaccination and coverage across the five counties shows analyzing population data against benchmarks (3.1k).