A data analysis project exploring revenue loss and operational risk in a tutoring business using Python, SQL and Power BI.

A practical look at how I use Python in data analysis when Excel is not enough — from scenario testing to deeper analytical insights.

A reflection on why “junior” doesn’t mean “inexperienced” and how diverse backgrounds strengthen analytical teams.

For me, SQL is not just about extracting data — it’s a way of turning vague business questions into clear, testable insights.

This project explores how clear, practical MI reporting can support day-to-day operational decisions by making workload, backlog and service performance easier to understand.

Before dashboards or visuals, I use Excel as a thinking space - to explore data, test assumptions and understand the problem I’m trying to solve.

Before opening any tools, I focus on understanding the problem, the decision behind it and what “good enough” really means for a data analysis project.

Being effective in data analysis isn’t about knowing everything - it’s about asking the right questions and focusing on decisions that matter.

A Business Analysis case study exploring how attendance patterns, capacity utilisation and staffing decisions influence day-to-day operations in a UK nursery.