Level Up Log

Lately, I've found myself in situations that felt a bit out of my comfort zone, and it got me thinking about how I interact with people and present myself, even in small, everyday moments like speaking up in a discussion, introducing myself to someone new, or walking into a networking event where I don't know anyone. I recently came across the idea of “channelling someone” again while listening to The Diary of a CEO podcast with Vinh Giang. It wasn’t completely new to me. When I was working as a musician, I would often "channel" a particular musician while playing. Someone whose tone or energy matched what I needed in that moment. But I had never thought of applying the same idea outside of music. On the podcast, Vinh explains how we can borrow confidence from someone we admire. Not in a "fake it till you make it" way, but more like using someone else’s energy as a prompt to shift how you carry yourself. You’re not pretending to be them. You're simply ...

I started Data Camp's Associate Data Analyst in SQL career track at the end of March and expected it to take about 39 hours, since that’s what the estimate said. But in the end, it was closer to 45 hours and honestly, it was worth it. Not just because I finished the course or got the certification, but because of how much more clear SQL feels now, especially compared to when I was learning it for the first time during the Google Data Analytics course. Learning the Order of Execution One of the most helpful parts of this course was the way it explained concepts in a logical order. In particular, understanding the order of execution helped me finally get the difference between WHERE and HAVING. During the Google course, I couldn’t figure out why one worked and the other didn’t. It was never clearly explained that the filtering happens at different stages: WHERE filters rows before the grouping, and HAVING filters after. Once I understood the order of execution, it just clicked! M...

In a previous blog post about the Stanford Introduction to Statistics course, I mentioned that I’d be revisiting a few topics that took me a little longer to wrap my head around. This post is exactly that. A way for me to break down topics, not just to clear things up for myself, but also to create something I can revisit whenever I need a quick refresher. So here are the topics I'm going to cover: Law of Large Numbers vs Central Limit Theorem Significance Level vs. P-value Confidence Level vs Confidence Interval Standard Deviation vs Standard Error Z-test vs T-test 1. Law of Large Numbers (LLN) vs Central Limit Theorem (CLT) Both are foundational ideas in statistics and often mentioned together, but they’re doing two very different jobs. LLN says that as your sample size increases, your sample mean gets closer to the true population mean. CLT explains that regardless of your population’s distribution, the sampling distribution of the sample mean becomes approximately normal a...

When I first got into data, I assumed that the most important part was the data itself. Finding the right numbers, doing the right analysis and picking the right chart. But after reading Storytelling with Data by Cole Nussbaumer Knaflic, I realized there’s a whole other layer to good data work: telling a story that actually connects with people. This book changed the way I think about presenting data. I picked it up expecting a technical guide, and it is that, but it also dives deep into how we communicate, persuade, and get people to care. Here are a few of the big takeaways that stood out to me whilst reading. Start with the Who and the Why Before you even touch a chart or a slide, you have to ask: who is this for? And why does it matter to them? The book makes a big distinction between exploratory and explanatory analysis. Exploratory is the part we often focus on—trying out different things, testing hypotheses, figuring out what’s interesting. But when it's time to p...

Over the last few weeks, I’ve been starting my mornings by reading for just 10 minutes a day. I recently finished You Are a Badass by Jen Sincero, and it’s been the perfect way to set the tone for the day, getting me into that “go get it” mindset. I wanted to share some key takeaways that really stuck with me. The Power of Your Thoughts – Focus on what you want, not what you fear. Visualising Success – Train your mind to expect success. Decide, Don't Just Wish  – Act like success is a matter of when , not if . The Power of Your Thoughts One of the biggest ideas in the book is that we’re all vibrating energy, and we attract whatever frequency we put out into the world. That made me reflect on how I’ve approached things up until now. For a long time, I had this habit of always preparing for the worst. Even if something only had a slim chance of going wrong, I’d focus on it. I wouldn’t let myself fully believe things could work out because I was too afraid of being disappoint...

Over the past week, I spent a total of 31 hours completing both the Excel  Fundamentals and Data Analysis with Excel  Power Tools skill tracks on DataCamp. Having enjoyed Excel during the Google Data Analytics course, I was excited to further develop my skills. Why I Enjoyed Learning Excel Excel has always been one of the more intuitive tools for me. Since I already use it to track personal data, picking up new concepts felt easy and exciting. The visual and interactive nature of Excel makes it easier to grasp compared to some other tools. I also really appreciated the pace of the DataCamp courses . They move quickly enough to stay engaging without feeling repetitive, which kept me motivated. M Language Difficulties The final section of the Power Tools course introduced M Language , and it was a steep learning curve . While I appreciated the introduction to more advanced concepts, I found the last exercises particularly challenging—I felt like I was following instruc...

At the end of February, I took the next step in my data analytics journey: the Stanford Introduction to Statistics Course on Coursera. Since I had just completed the Google Data Analytics Professional Certificate Course that same day, I couldn't help but find myself comparing the two. What I didn’t expect was just how different the experience would be. A More Intense Learning Experience The course is labelled as beginner-friendly and estimated to take around 14 hours to complete. In my case, it took closer to 18 hours—partly because the content was quite dense and partly because I wanted to ensure I truly understood each concept before moving forward. With the Google course, I was able to move quickly, watching most sections at 2x speed. That wasn’t an option here. I frequently had to pause, re-watch explanations, and work through my own examples to fully grasp the material. While some concepts were familiar from previous studies, I aimed to go beyond just recalling formulas. I w...

When I first reached the case study of the   Google Data Analytics Professional Certificate , I felt completely unprepared. The idea of working on a full project from start to finish seemed overwhelming. A big part of me wanted to put it off, thinking I should learn more before even attempting it.  But after some reflection, I decided to just go for it whilst keeping a few key things in mind: It’s not going to be as good as I want it to be.   And that’s okay. It’s my first time, so of course it won’t be perfect. The only way to get better is to actually do it, no matter how unready I feel. I’ll get to experience the full process.   This was my first chance to work through an entire project on my own. Learning how to ask the right questions, make decisions, and problem-solve along the way are some hugely valuable skills which I can only gain through hands-on experience. I’ll learn more than I would from just following tutorials.   Doing a case study forces me to ...

Last week, I wrapped up the Google Data Analytics Professional Certificate , and I wanted to take a moment to share my experience and thoughts. This course marked my first big milestone in my career transition into data analytics, so I thought it would be helpful to reflect on what I learned, what worked well, and what didn’t. This post covers my experience with the course up until the final case study—I’ll be dedicating a separate post to the capstone project next week. What I Liked About the Course A Focus on Soft Skills One thing that really stood out to me about this course was its focus on soft skills before diving into technical ones. Instead of immediately jumping into tools like Excel, SQL, and Tableau, the course started with topics like effective communication , collaboration , and how to ask good questions . As someone with no prior experience in a corporate job, I found this approach really helpful. It gave me a better understanding of what to expect in a professional...

A couple of years ago, I read   Deep Work   by Cal Newport. I remember really enjoying it, but like a lot of books I’ve read, I didn’t actually put much of it into practice. Recently, though, that’s changed. Now that I’m studying again to switch careers and re-skill myself, I’ve been actively trying to implement more of these ideas into my daily routine. On top of that, I watched Ali Abdaal’s YouTube video,   6 Habits to Make 2025 Your Best Year Yet , where he talks about timing focused work sessions and tracking them. Between these two influences, I’ve built a new system to keep myself accountable, stay motivated, and—because I’m training to become a data analyst—have fun looking back on the data I collect. It’s been both eye-opening and humbling to see exactly how much—or how little—I’ve actually been working. Why I Call It Deep Focus Cal Newport calls it   Deep Work , but I’ve decided to refer to it as   Deep Focus . The reason for this is that I don’t just t...

I’ve always been into learning and personal development—whether it’s diving into insightful YouTube videos, reading motivational books, or picking up new ways of thinking from the people around me. The fun and novelty of it all gave me the feeling of progression and expansion. But there was one recurring issue… I'd spend hours exposing myself to all this new information, but not  fully  processing   or   applying   it to my life. I tried jotting down a few notes here and there, but they’d often get buried and forgotten, and before I knew it,  I was onto the next new thing. Over time, I realised all this consumption wasn’t actually moving me forward. Sometimes, I’d come across ideas that were truly fascinating,  inspirational, and  life-changing, but soon enough, I'd forget all about it.  It would feel like nothing had changed—like I never read the book or watched the video at all, and in the end, it just amassed to wasted time. That’s why I’m...