The Tech Skills I Thought I’d Never Learn (And How I Did Anyway)
- Bre Ethridge
- Jan 10
- 8 min read
Updated: Jan 10
If you’d told me a five years ago that I’d be writing SQL queries, automating workflows in Power Automate, or building interactive dashboards in Power BI, I’d have laughed—maybe even panicked a little. Back then, the thought of learning those tools felt overwhelming, like I’d need to be some kind of tech wizard to make it work. Spoiler alert: I’m no wizard, but I did figure it out. And if I can do it, anyone can.
So, let me share the journey—the struggles, the breakthroughs, and the lessons I learned along the way.
The Fear of the Unknown: My First Encounter with SQL
The first time I opened a SQL editor, it felt like stepping into a foreign land where I didn’t speak the language. SELECT? JOIN? HAVING? It was all gibberish. And yet, I had a task to complete—pull some basic data. To say I was intimidated is an understatement.
Interestingly, this wasn’t my first coding rodeo. My first-ever foray into programming was tinkering with JSON for a video game mod I wanted. I still remember the rush of making that mod work and realizing I could actually create something with code. But transitioning from JSON to SQL was like switching from playing guitar to conducting an orchestra. The tools, the syntax, the entire structure—it was all so different.
I started with MySQL, where I spent hours (sometimes days) trying to write the simplest queries. When I switched to PostgreSQL, I fell in love. It was cleaner, more powerful, and just... better (at least for me). But let’s be honest: no matter which flavor of SQL you use, the learning curve is steep.
The hardest part? SQL has a vast library of syntax, and trying to remember it all is a losing battle. Early on, my queries were messy, clunky, and full of unnecessary notes. I’d write 10 lines of code for something that could be done in two. It wasn’t pretty, but it worked. Over time, I learned the value of writing clean, efficient queries—and that’s where tools like W3Schools SQL Guide became my lifeline. I still use it today. It’s a fantastic resource, updated regularly, and perfect for when you need a quick refresher.
What really made SQL click for me was realizing that it’s okay not to know everything. Instead of memorizing syntax, I focused on understanding concepts. Why use a JOIN? When do you need a subquery? This shift in mindset—from memorization to comprehension—made all the difference.
How I Made SQL Work for Me:
Start with the Basics: I didn’t try to tackle complex queries right away. Instead, I focused on mastering simple SELECT statements and gradually built from there.
Practice in a Sandbox: I found sample databases online (mainly Kaggle) and practiced running queries in a safe environment. This gave me the freedom to experiment without pressure.
Leverage Resources: W3Schools and other online platforms were invaluable for quick syntax lookups and examples. Even now, I rely on these tools to refresh my knowledge.
Trial and Error: Not every query worked on the first try (or the second. . . maybe even the third 😅), but each failure taught me something new. Debugging became one of my best teachers.
Formal Training: Enrolling in the Thinkful program gave me structured learning, but I also supplemented it with LinkedIn courses and my own research.
Those small wins—like the first time I successfully joined two tables—kept me motivated. With time and practice, SQL transformed from an intimidating hurdle to one of my strongest tools.
Python: A Love Story in Code
While SQL felt like a necessary skill, Python became a passion. My introduction to Python came through the Chegg Skills program, and it opened up an entirely new world of possibilities.
I’ve used Python for all kinds of fun projects, like connecting APIs for data pulls, web scraping, automating repetitive tasks, cleaning and preparing data, and even building the base for a text-based video game. I prefer using Visual Studio Code (VS Code) instead of the basic Python interface. The clean line structure and colorful layout make everything feel more organized and easier to read—it’s a game changer for keeping code structured and my head clear.
What I love most about Python is its versatility. With libraries like Pandas and NumPy, I’ve tackled everything from data manipulation to analysis. For web scraping, Beautiful Soup has been my go-to, and when I wanted to dabble in game development, Pygame made it possible. I’ve even explored more advanced libraries like PyTorch for natural language processing (NLP) and psycopg2 and SQLAlchemy for handling SQL queries seamlessly within Python. Python feels like a Swiss Army knife, capable of addressing so many challenges in creative ways.
But it wasn’t always smooth sailing. My first attempt at writing Python scripts was a mess. Syntax errors popped up everywhere, and debugging felt like solving a riddle in a language I barely understood. It was humbling, to say the least.
How I Made Python Work for Me:
Experimenting with Projects: From connecting APIs to pulling live data to writing automation scripts for data cleaning, I kept testing Python’s capabilities. These real-world projects gave me the confidence to keep going.
Using Online Resources: W3Schools was an incredible starting point, and Reddit communities like r/learnpython always had helpful advice. GitHub became a treasure trove of open-source projects that inspired new ideas.
Diving into Libraries: Pandas and NumPy became staples of my workflow, but I also learned tools like Jupyter Notebooks for interactive coding sessions and psycopg2 for managing SQL databases. Each library opened up new possibilities.
Sticking to Tools That Work: VS Code was a personal preference that elevated my Python experience. Its organization and readability kept me on track, especially during longer sessions.
Always Learning: Even after getting comfortable, I continued to explore. From web scraping with Beautiful Soup to using PyTorch for NLP, I kept challenging myself to learn new libraries and techniques.
Now, Python is my go-to for personal projects and creative exploration. Whether it’s preparing data for visualizations in Power BI or automating a tedious process, Python is always up to the task. And while I prefer to handle visualizations in Power BI or Tableau, Python’s data manipulation tools remain unmatched.
Power BI: Turning Data into Stories
When I first saw a Power BI dashboard, my eyes lit up like a Christmas tree. I was amazed. My first words were, "It’s like Excel but on steroids!" The way it transformed data into interactive visuals was mind-blowing, and I couldn’t wait to try it.
What helped me pick up Power BI so quickly was its familiarity. Power BI uses Power Query, which I already knew from Excel. And while the formulas are called DAX instead of formulas, the structure is similar enough to make the transition easy. Still, I didn’t try to memorize everything. Instead, I leaned heavily on resources like Microsoft Learn’s DAX function reference, which I still use as a cheat sheet today for specific functions I can’t quite recall.
The hardest and most enjoyable part of Power BI for me is figuring out which visualization best represents the data I want to showcase. It’s an art form—telling a story with data in a way that’s clear and engaging. Designing dashboards and creating backgrounds is where I truly have the most fun. I even use Figma to craft custom visuals, something I’ve incorporated into several of my projects.
To keep my skills sharp, I follow some favorite YouTubers for both learning and design inspiration:
Learning Power BI: Alongside Guy in a Cube, Alex The Analyst has been instrumental in helping me refine my technical skills.
Dashboard Design: Your Own KPI and How To Power BI are phenomenal. They focus on creating functional yet visually stunning designs. Both use Figma, so I get to learn both dashboard and design techniques in one place.
Power BI has become my absolute favorite tool for turning data into a beautiful, compelling story. I’ve often said this because it’s true: I already see data as a story, and Power BI lets me bring that story to life for others. Although Power BI is my preferred tool, I also know and use Tableau. Once you learn one, the other becomes easier, so I recommend exploring both to see which fits your workflow best.
How I Got Through It:
Learn by Doing: My first dashboards were far from perfect, but I dove in headfirst and improved with every iteration.
Mastering DAX: I didn’t try to memorize DAX formulas. Instead, I relied on Microsoft’s DAX reference guide to help me get specific outcomes.
Finding Inspiration: Watching YouTubers like Your Own KPI and How To Power BI opened my eyes to what’s possible in terms of both design and functionality.
Experimentation: I tested different layouts, visuals, and storytelling approaches, creating dashboards just for fun to refine my skills.
Feedback and Collaboration: Sharing my dashboards with colleagues and listening to their feedback taught me how to align my work with stakeholder needs.
Today, Power BI feels like second nature, a perfect blend of technical and creative work. Every time someone uses a dashboard I’ve created and finds it useful or insightful, I feel that same initial excitement all over again
Power Automate: From “What’s That?” to “Look What I Built!”
Power Automate wasn’t just a challenge—it was completely off my radar until I needed it for a project. The task? Automate a repetitive process involving email notifications and document approvals. Easy, right? Not for someone who’d never even heard of “triggers” or “flows.”
My first attempt resulted in a flow that didn’t flow. Emails went to the wrong people (oops), approvals didn’t trigger (double oops), and I seriously considered giving up. But with persistence (and a lot of Googling), I slowly began to understand how the pieces fit together.
Once I got the basics down, I started thinking bigger. Innovation and creativity are always running nonstop in my mind, so I challenged myself to go beyond the templates. The first real flow I built was a simple form response notification, but I didn’t stop there. I turned that notification into an adaptive card posted in Teams—and this was before I knew about the Adaptive Card Designer. I manually built it with JSON, and when it worked, I was hooked.
Then came my wildest project: building an entire ticketing system in Power Automate. Using Forms, SharePoint Lists, Outlook, and Teams connectors, I created a system where users could submit tickets, track updates, and receive notifications—all automated. It was far from perfect at first. I’ve gone back to that flow many times to clean it up, make it more efficient, and tweak the structure, but it taught me so much about what Power Automate can really do.
How I Got Through It:
Templates to the Rescue: Templates are a great starting point, but I quickly pushed past them to explore what else was possible.
Dive into Data Types: Understanding variables and data types like strings, booleans, and arrays was key to building more complex flows. For beginners, I’d highly recommend starting here.
Use Community Resources: Microsoft Learn and the Power Community were lifesavers. The shared examples and advice helped me troubleshoot and improve my workflows.
Keep Iterating: I frequently go back to old flows to make them more efficient and organized. Each revisit teaches me something new.
Teaching Others: Hosting training sessions for other departments has solidified my expertise and helped me think of Power Automate in new ways.
Now, automation feels second nature. Someone asks, “Can we automate X?” and my immediate response is, “Yes, let me save you time.” My experience with Power Automate has not only made my own work more efficient but also helped teams across my organization embrace automation. There’s still so much I want to learn, like Azure and Graph APIs, but for now, I’m proud to be seen as the go-to “expert.”
The Biggest Lesson: You Don’t Have to Know Everything
Looking back, the most important thing I’ve learned is that you don’t need to have all the answers upfront. It’s okay to ask questions, make mistakes, and learn as you go.
These tools felt impossible at first because I was expecting perfection from day one. But growth isn’t about being perfect—it’s about being persistent. Each small win builds confidence, and before you know it, the skills that once seemed out of reach start to feel manageable.
During all of this, I continued to practice like crazy. At work, I used Power BI, wrote simple expressions in Power Automate, and explored advanced Excel. In my free time, I built a website and honed my skills in SQL, Python, Tableau, and SharePoint. I’ve even created dashboards in Excel, and I can’t wait to showcase those projects soon.
So, to anyone facing their own “tech mountain” right now: keep climbing. It’s worth it.
What About You?
What’s a tech skill you thought you’d never learn? How did you get through it? I’d love to hear your stories—share them in the comments!
I loved reading this—it’s so inspiring to see how far you’ve come! Your story reminds me of my own journey with web development. If you’d told me a few years ago that I’d be writing HTML, CSS, and JavaScript, I would’ve laughed nervously and said, “No way.” Coding felt so out of reach, like it was only for geniuses who lived and breathed tech.
But one day, I decided to just try. I started small—learning basic HTML tags and experimenting with CSS to make things look pretty. I still remember the first time I got a button to change color when I hovered over it. It was such a small thing, but to me, it was like magic!
Of course,…