Ibuildthepipelinesthatturnrawdataintodecisions.

A Stack Overflow Developer Survey analysis that turns technology adoption signals into hiring and learning priorities.

Question

Which programming languages, databases, and platforms are stable today, desired tomorrow, and worth investing in?

Outcome

Built a Cognos-backed report covering language demand, database shifts, cloud adoption, and developer demographics.

Built an automated reusable ETL pipeline in Pandas to clean and transform a 7,000+ row telecom dataset, handling hidden nulls, type casting, target binarization, and tenure cohort engineering. Built an interactive Power BI dashboard to analyze customer churn trends.

Question

How can we identify customers who are likely to churn and take proactive measures to retain them? What are the most important factors that influence churn?

Outcome

Quantified $139K in at-risk monthly recurring revenue and identified Month-to-Month contracts as the primary churn driver, producing 4 actionable retention recommendations.

A scheduled ETL pipeline that ingests daily equity data from the Alpha Vantage API, loads it into Azure SQL, and surfaces risk through an interactive Power BI monitoring dashboard.

Question

How can we track and compare the daily risk profile of multiple equities in near real time, from raw API data all the way to a decision-ready dashboard?

Outcome

Built a Python ETL pipeline for 5 tickers automated via GitHub Actions, engineered a 7-day rolling volatility feature (NVDA: 0.37 vs JNJ: 0.08), and delivered a DAX-driven dashboard tracking price, returns, and volatility across $29bn in total volume.

A gamified fitness tracking app where workouts become quests and user progress becomes a measurable retention loop.

Question

How can a fitness app make daily training feel rewarding enough that users return without being pushed?

Outcome

Analyzed engagement and feedback signals tied to a 40% lift in daily adherence, 30% stronger active session participation, and 25% better goal consistency.