Data Analytics Work Samples

Public Tableau

Please see my Public Tableau page for Tableau Dashboards and Stories. Data visualizations include:

  1. Exploring US County Health Data: Health struggles are interconnected with economics. This study used Tableau to uncover correlations between economic and health factors across the US. Findings inform intervention and policy approaches directed at improving public health.
  2. NHS Hospital Admission Data: To meet client needs in terms of staffing and rooms, hospitals must plan. This Tableau story explores NHS Admitted Patient Care Main Speciality data reporting specialty-specific measures. Reports may help administrators in long-term scheduling and improving responsiveness to clients.
  3. Deaths Related to Drug Overdoses: America faces ongoing challenges with drug addiction. This study uses Tableau to explore deaths associated with drug overdose by U.S. state, year, and type of drug. Findings inform public health policy approaches and goals.

Data Analytics program coursework

The projects linked below were performed using various technologies as part of the Data Analytics program coursework.

  1. Using SAS® Studio to understand economic and health factors that impact youth suicide in Colorado. GitHub. PDF.
    • Utilizes two data sets:
      • United States Health Resources and Services Administration County-level Area Health Resources Files (https://data.hrsa.gov/data/download)
      • Colorado Department of Public Health and Environment Colorado Health Indicators (https://www.colorado.gov/pacific/cdphe/colorado-health-indicators)
    • Uses GoogleSheets and SAS® Studio to perform Extract, transform, and load (ETL) functions.
    • The data were explored numerically and visually using SAS® Studio and RapidMiner.
  2. Using R to understand correlations between economic and health measures across American counties using population data. GitHub. PDF. Tableau Public.
    • Analyzes the Robert Wood Johnson Foundation’s “US County Health Rankings” dataset (2014) in CSV format.
    • Investigates associations between economic and health factors at a county level, as well as the interaction of location on those economic and health measures.
    • Uses R to plot the data in a variety of forms and to calculate linear regressions.
  3. Using Tableau® to build a dashboard visualizing national population data. PDF.
    • Analyzes the same Robert Wood Johnson Foundation’s “US County Health Rankings” dataset (2014).
    • Uses Tableau® to analyze health and economic measures against location using best practices for data visualization.
  4. Leveraging Metrics to Improve Project Performance. PDF.
    • Explores several case studies to underscore the importance of using well-designed dashboards to support effective project management.
  5. Using SAS® Enterprise MinerTM to predict pharmaceutical demands. PDF.
    • Uses a fictional dataset provided in multiple CSV files for a predictive analytics project.
    • GoogleSheets was used to clean and transform the data, including computing several derived fields.
    • SAS Enterprise Miner was used to impute missing values and transform skewed data. It was then used to develop and compare viable regression models. Finally, SAS Enterprise Miner was used to create an ensemble model by combining the two best performing models.