Snapshot
I collaborated with the Business Intelligence team on data gathering, cleaning, integration, risk identification, and dashboard delivery while operational needs evolved.
The situation
Application and operational data needed to remain consistent and accessible as a health-tech business changed.
The problem
Backend systems, the main database, and stakeholder reporting required dependable synchronization, freshness, and clear risk escalation.
My responsibility
I supported integration and data quality, investigated risks, and translated operational data into stakeholder-facing reporting.
Approach
- Synchronized backend systems with the main database.
- Maintained data quality and freshness.
- Identified and escalated data risks.
- Developed and maintained more than 10 dashboards and reports.
Solution
The work combined data integration, monitoring practices, and stakeholder-facing reporting across Metabase, Looker Studio, and BigQuery. Published visuals are cropped to remove row-level records and contact fields.
Doctor registry pipeline
I structured a repeatable path from public doctor-registry extraction through validation and deduplication into BigQuery. The reporting layer exposed aggregate qualification and university distributions while keeping row-level registry records outside the public portfolio.
Prescription follow-up operations
I also supported visibility over prescription recall queues. The workflow separated incoming prescriptions, waiting or hold states, assigned follow-up, and recorded resolution so operational teams could inspect pending work without relying on an undifferentiated row-level export.
Outcome
The deliverables supported faster operational visibility and decision-making. Claims about delivery-cost effectiveness and aggregator growth are omitted because their definitions and evidence have not been verified for publication.
What I learned
In operational healthcare analytics, reliable definitions and escalation are as important as dashboard design. Public disclosure must also protect sensitive data.