Hi everyone! I'm a senior business analyst with a solid background in audit and a decade of experience in analysis. I'm quite proficient in Excel, utilizing functions and VBA regularly. However, my team is finally moving toward handling big data, and I'm realizing that Excel has its limitations. I do have some knowledge of SQL and Python, but I definitely feel more comfortable in Excel. I'm at a crossroads—should I fully switch to Python for my projects, especially since around 75% of my work is currently manageable in Excel? Are there others who have made this transition? I'd really appreciate any advice you can share!
5 Answers
Thanks all for your responses! I see that it’s good to use both Excel and Python depending on the task at hand. I've been considering which projects truly warrant a switch, and I think focusing on Python for the heavier lifting with larger datasets might be the way to go. Appreciate the advice!
If Excel is working well for you, there’s no need to switch completely. VBA can handle a lot for smaller tasks, but for data that exceeds Excel's capabilities or for complex processes, Python with libraries like pandas really shines. I use both tools depending on the job—Excel for quick, simple tasks and Python for anything that requires deeper analysis or larger data handling.
Excel can be way faster for quick tasks, so don't dismiss it entirely! If you're keen on improving your Python skills, consider tinkering with converting some of your spreadsheets into Python scripts during your free time. Start with frameworks like pandas and use notebooks—those are key for beginners. But for massive datasets, sticking with SQL is usually a better choice; it really depends on your comfort level and the specifics of your projects.
Also, try using Spark if you're dealing with larger datasets; it really helps!
Honestly, Python isn’t as intimidating as it seems! If you invest just a couple of months in learning it, you could add a powerful tool to your skill set. Don’t feel like you’re lacking knowledge—you're probably more capable than you think! Keep practicing, and soon you'll see how beneficial it can be compared to relying only on Excel.
I switched from being an 'Excel slave' to working with Python for data engineering. My advice is to start with the basics of pandas. Pick a specific project to migrate rather than trying to do everything at once. Excel can be great for prototyping, but once you define your inputs and outputs clearly, Python will make things easier. Break down your tasks step-by-step and test each part independently. Logging is super helpful too! Just take it one step at a time and don’t overwhelm yourself with trying to do it all at once.
I also recommend exploring polars if you're new to Python and already have SQL experience. It might be beneficial for you.
And don't forget to try using Jupyter Notebooks! They really help to visualize results quickly as you work through the data.
Totally agree! SQL is super useful, especially when the data gets large. But for transitioning, start with the basics in Python.