Overview
Designed and developed interactive data stories that transformed complex pharmaceutical datasets into clear, actionable insights for executive leadership and board presentations. Focused on market trends, patient outcomes, and operational efficiency metrics.
Challenge
Pharmaceutical data was trapped in complex tables and raw datasets that executives struggled to interpret. Key issues:
- Data existed in silos across systems
- No standardized visualization approach
- Insights buried in spreadsheets
- Lack of interactive exploration capabilities
Solution
Data Integration
- Built unified data models combining sales, clinical, and operational data
- Automated ETL pipelines using Python and Pandas
- Created master data repositories in SQL Server
- Implemented data quality checks and validation
Visual Storytelling
- Designed Tableau dashboards with narrative flow
- Created interactive drill-down capabilities
- Implemented color theory for data hierarchy
- Built mobile-responsive views for on-the-go access
Key Visualizations Created
- Market share trends vs. competitors
- Patient adherence patterns by demographic
- Drug efficacy outcomes over time
- Supply chain optimization opportunities
- Clinical trial enrollment funnels
Design Principles
Clarity Over Complexity
- Limited color palettes (3-5 colors max)
- Progressive disclosure of details
- Clear call-to-action insights
- Annotation of key trends
Executive-Focused
- One-page summaries for board meetings
- Drill-down paths for detailed exploration
- Export capabilities for presentations
- Real-time data refresh
Business Impact
- $2M+ strategic investments informed by data insights
- 40% reduction in time spent preparing board presentations
- 95% executive satisfaction with data clarity
- Identified $750K cost-saving opportunity through supply chain optimization
- Improved patient outcomes through adherence trend identification
Technical Stack
- Visualization: Tableau, Power BI, Matplotlib, Seaborn
- Data Processing: Python, Pandas, NumPy
- Database: SQL Server, PostgreSQL
- Automation: Apache Airflow, Python scripts
- Collaboration: Confluence for documentation