Featured Projects
A selection of enterprise analytics products I have designed and delivered.
Digital Hub Dashboard
Provides insights to keep global and regional Digital Hub Management informed about all dimensions of the DH business.
- Developed the SQL data model utilized for the dashboard.
- Designed and implemented the dashboard.
- Collaborated with the Digital Hub team to define and establish KPIs.
3rd Party Software Dashboard
Evaluates org usage of third-party software usage, evaluate costs, and highlight opportunities for savings.
- Developed the SQL data model utilized for the dashboard.
- Designed and implemented the dashboard.
- Collaborated with Org Leaders to drive actionable changes.
Cloud Health Score — Risk2Action Report
Overview of customer health, movement of healthy to unhealthy accounts, and top critical alerts.
- Connected to existing data model.
- Designed and implemented the dashboard.
- Collaborated with the Global Renewals Process team to define and establish KPIs.
Partner Engagement Dashboard
Establish a foundation of data for the Partner Engagement Team.
- Developed the SQL data model utilized for the dashboard.
- Designed and implemented the dashboard.
- Collaborated with the Partner Engagement team to define and establish KPIs.
Adoption Analysis Report
Analysis of Entitlement Consumption by Contract-level data, Cloud Health Score & LPR Scoring & Adoption.
- Compiled and analyzed data and metrics for the report.
- Developed a PowerPoint report based on key metrics and data points.
- Presented key insights and findings derived from the report's metrics.
Market Sentiment Report
Summarize customer sentiment and feedback trends.
- Compiled data through a collaborative effort leveraging insights from multiple executive feedback.
- Designed and implemented the dashboard in SAC.
CPIT Portfolio Insights Dashboard
Executive-facing dashboard providing leadership with a real-time view of portfolio performance across all CPIT organizations — tracking delivery health, investment allocation, and strategic alignment in a single pane of glass.
- Designed end-to-end from data model to dashboard with no existing blueprint.
- Built on governed SQL views in SAP Datasphere surfacing KPIs across multiple portfolio verticals.
- Partnered directly with executives to define metrics and reporting structure.
Portfolio Hygiene Scoring Model
A 0–100 portfolio health score computed in SQL across four data quality dimensions — missing Technical Requirements, missing Investment Cluster tagging, missing parent-link relationships, and stale TR dates — surfaced in SAP Analytics Cloud with band-based executive indicators.
- Designed the scoring formula and all four dimension weights from scratch.
- Engineered the SQL logic in SAP Datasphere/HANA to compute scores at portfolio scale.
- Surfaced scores in SAC with color-coded bands (Excellent / Good / Needs Attention / Critical).
Intake Analytics Dashboard
Demand tracking dashboard built on the CPINTAKE Jira project, providing visibility into new intake volume, status distribution, and routing by vertical and component — giving portfolio managers a real-time view of the demand pipeline entering the portfolio.
- Engineered SQL views in SAP Datasphere to normalize CPINTAKE data by component and vertical.
- Built intake volume, aging, and status KPIs from scratch with no existing data model.
- Automated data refresh to ensure real-time demand visibility without manual intervention.
Meet in The Middle Dashboard
A personal analytics tool built to solve a real problem: finding the right neighborhood for a growing family by meeting geographically between two sets of parents. Users enter two zip codes and the dashboard surfaces every neighborhood within a 3-mile radius of the midpoint — ranked by affordability, school quality, crime rates, demographics, and long-term property value. Built end-to-end: web scraping via Power Automate, SQL data cleaning and storage, Python reverse geocoding via Google Maps API, and a multi-page Power BI report with live filters, interactive maps, and calculated mortgage estimates.
- Scraped real estate listings (Realtor.com), school ratings (GreatSchools), neighborhood coordinates, and crime data via automated Power Automate flows — bulk loaded into SQL with custom cleaning queries.
- Wrote Python reverse geocoding script using Google Maps API to assign zip codes to raw lat/long crime coordinates.
- Built a full mortgage estimator in DAX: P&I formula (6.97% rate, 20% down, 30-year term) + monthly property tax + insurance estimate, driven by county-level tax rates for Philadelphia, Montgomery, and Delaware Counties.
- Designed 5 dashboard pages: Overview, Neighborhood, Schools, Real Estate, and Single Neighborhood deep-dive view.
▶ Data Sources & Methodology
| Source | Coverage | Used For |
|---|---|---|
| Realtor.com | Oct 2024–Mar 2025 | Sold & active listing data |
| GreatSchools.org | Current | School ratings & type |
| U.S. Census | 2023 | Race, age, population, median income |
| Philadelphia Crime Data | 2024 | Crime type & offense counts |
| County Tax Records | 2024–2025 | Property & wage tax rates (Phila, Montco, Delco) |
| BankRate / Insurance Est. | Current | Mortgage rate (6.97%) & insurance input |
- Neighborhood radius: Any zip/neighborhood within 3 miles of the midpoint between two entered zip codes.
- Schools in area: Within 2-mile radius of zip; public schools additionally filtered to same county. PK–12 only; daycares excluded. Private schools unrated by GreatSchools — listed as "Private" and counted as high-quality.
- Mortgage formula: P&I (20% down, 6.97% APR, 30-year) + monthly property tax + monthly insurance estimate. County millage applied to assessed value (1 mill = 0.001).
- Crime rate: Offenses per type ÷ population × 100,000.
- Price difference %: (Sold price − earliest listed price) ÷ earliest listed price.