Learning Journey

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

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.

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.

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

For me, being a data analyst is about asking the right questions, understanding context, and turning data into meaningful insights.

As part of my data and business analysis learning path, I completed two very different certifications: BCS Business Analysis Foundation and CompTIA Data+.

When I started learning data analysis, I thought the hardest part would be Python or statistics. I was wrong. The hardest part was knowing where to start , what actually matters , and how not to get lost  in the data. Over time, through courses and hands-on projects, I developed a simple approach that helps me stay focused and make sense of what I’m analysing. This post sums up how I usually work. 1. Defining the Problem First (Before Touching the Data) Before opening Excel,