All Posts

A personal reflection on entering data analytics - and why experience doesn’t always “count” until it has the right job title.

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

A practical reflection on why data analysis doesn’t start with data — but with unclear business problems that need to be understood first.

A reflection on why reporting alone is not enough - and why the real value of analysis starts when decisions are made.

A practical reflection on how stakeholder requests often differ from actual business needs — and why understanding the problem matters more than delivering the output.

When data doesn’t give a clear answer, the goal is not to force one - but to make the decision clearer by showing trade-offs, risks and possible scenarios.

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 small data analysis project comparing Data Analyst job postings in the UK and Poland using LinkedIn data. The Tableau dashboard explores competition levels, experience expectations and the most commonly requested analytical tools.

A data analysis project exploring how discount levels influence profitability using Python and a Power BI dashboard to identify an optimal discount strategy.

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

A clinical trial case study exploring how statistical analysis translates into clear, decision-ready conclusions.

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

A good Power BI dashboard isn’t about showing everything - it’s about highlighting what matters and supporting clear, confident decisions.

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.

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

At the beginning, I thought mistakes meant I wasn’t good enough. Over time, I realised they were the moments that taught me the most about real data analysis.

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

Good data analysis isn’t about analysing everything. It’s about understanding what truly matters and knowing what to leave out.