Data Analytics – Shiel Yule

Just a few short months ago, the world of data analytics felt like a vast, uncharted ocean. Now, after completing Google’s Data Analytics Professional Certificate (or at least the 12+ modules that make up the learning path – more on that later!), I feel like I’ve charted a course and am confidently navigating those waters. It’s been an intense, exhilarating, and sometimes head-scratching journey, but one I wouldn’t trade for anything.

My adventure began in October 2024, and by February (this week) 2025, I had conquered (most of) the learning path. Conquer is the right word, because it was definitely an intense learning curve. 2000’s dev junior SQL skills? Yeah, they got a serious dusting off. And my forgotten Python, which was starting to resemble ancient hieroglyphics? Well, let’s just say we’re on speaking terms again.

The modules covered a huge range of topics, from the foundational “Introduction to Data Analytics on Google Cloud” and “Google Cloud Computing Foundations” to more specialized areas like “Working with Gemini Models in BigQuery,” “Creating ML Models with BigQuery ML,” and “Preparing Data for ML APIs on Google Cloud.” (See the full list at the end of this post!) Each module built upon the previous one, creating a solid foundation for understanding the entire data analytics lifecycle.

But the real stars of the show for me were BigQuery and, especially, Looker Studio. I’ve dabbled with other data visualization tools in the past (mentioning no names… cough Microsoft cough Tableau cough), but Looker Studio blew me away. It’s intuitive, powerful, and just… fun to use. Seriously, I fell in love. The ease with which you can connect to data sources and create insightful dashboards is simply unmatched. It’s like having a superpower for data storytelling!

One of the biggest “aha!” moments for me was realizing the sheer power of data insights. Mining those hidden gems from large datasets is incredibly addictive. And the fact that Google makes it so easy to access public datasets through BigQuery? Game changer. It’s like having a data goldmine at your fingertips.

This learning path has ignited a real passion within me. So much so that I’m now pursuing a Data Analysis Diploma, which I’m hoping to wrap up before June. And, because I apparently haven’t had enough learning, I’m also signing up for the Google Cloud Data Analytics Professional Certificate. I’m all in!

I have to say, the entire Google Cloud platform just feels so much more integrated and user-friendly compared to the Microsoft offerings I’ve used. Everything works together seamlessly, and the learning resources are top-notch. If you’re considering a career in data analytics, I would wholeheartedly recommend the Google path over other options.

I’m especially excited to dive deeper into the machine learning aspects. And the integration of Gemini? Genius! Having it as a code buddy has been a huge help, especially when I’m wrestling with a particularly tricky SQL query or trying to remember the correct syntax for a Python function. Seriously, it’s like having a data analytics guru by my side.

Stay tuned for future posts where I’ll be sharing more about my data analytics journey, including tips and tricks, project updates, and maybe even some data visualizations of my own!

Coursera do an official course = https://www.google.com/url?sa=E&source=gmail&q=https://www.coursera.org/professional-certificates/google-data-analytics – this you get a recognised formal professional certificate.

Or jump into Google Cloud Skills Boost: https://www.cloudskillsboost.google/ and get yourself a Cloud account and friendly with Gemini.

Modules Completed: