Why Excel Matters (And Pitfalls to Consider)
Pro's and con's to this ever popular data tool
Hey everyone 👋
Let’s talk about Excel.
It’s quite a polarizing tool. Some love it. Some hate it. And it’s been the butt of many a data joke.
Don’t believe me? Check out these memes.
Funny, right? And honestly kinda true.
But with all its limitations, I still believe it is a foundational tool that every data analyst should become proficient in.
The reason?
It’s still a staple tool for so many businesses. Let me humor you with one more meme…
All roads really do lead back to Excel at some point.
So it’s a good idea to get comfortable with this tool.
Excel was the gateway tool for me in my transition to analytics.
In my corporate job before data, I wanted to get really good at Excel to stand apart from the crowd. And I did.
When I got my first Business Analyst job, these Excel skills came in WAY handy and blew my boss away, even though I was still using other tools in the role regularly.
So I’d like to explain some key reasons why you should invest time in getting good with Excel.
But I’d also like to mention some things to watch out for.
Pros
1 | Excel formula logic will make learning other coding languages easier
A lot of formula logic that you see in Excel carries over into other coding languages.
Aggregations, IF and nested IF statements, even joins (equivalent to XLOOKUP in Excel). While the syntax will usually be different between tools, the logic is often very similar.
Developing skills with Excel formulas sets a great foundation for any analyst.
2 | It’s incredibly versatile
You really can do just about everything in Excel. I like to call it the Swiss Army Knife of data. You can create dashboards, perform exploratory analysis, clean data, code with VBA, and now they’ve even introduced Python into Excel.
While certain stand-alone tools may be more powerful at specific functions, Excel can do a pretty decent job at most things. It’s the ultimate ad-hoc analysis tool.
Skills in Excel visualization, conditional formatting, and Macros can go a very long way in impressing your manager and colleagues.
3 | It’s not going anywhere
Excel is the most widely used data tool, and it’s used for literally everything. As the memes above suggest, it’s carrying a lot of weight worldwide. And when you’ve seen what I’ve seen behind the veil of some companies, you know that it’s not going anywhere any time soon.
Things to Consider
1 | A lot of companies over-invest in it
A couple of those memes above ring true here. Many companies often cling to Excel long after they’ve exceeded its limits. I’ve witnessed this firsthand but friends of mine who are consultants see it all the time too.
It’s easy to get comfortable with Excel and a lot of companies hang on to it because it’s what they know, even if it’s no longer the best tool for the job.
2 | It’s powerful….but not that powerful
Excel has many limitations. Its row count is just over a million (see the meme above), but it starts slowing down well before that row number.
It really can’t hold that much data and it starts crashing once it begins reaching its threshold.
When you think about it, it’s just a simple spreadsheet tool, but people often treat it like a database or information hub; dumbing tons and tons of data into it when it was never meant to hold that much.
Excel is great, but understand that it has its limits.
3 | It’s easy to hide behind
This one might sting a little, but it’s a bit true. I was a bit guilty of this early on as well. A lot of new and aspiring analysts will wave the Excel flag high when they don’t have that much working experience with other tools.
Not necessarily a bad thing, but when you begin experiencing other tools in real business scenarios, it shapes a more holistic view of the modern tech stack.
But at the end of the day, it’s not the tools that make the analyst. Even if you just use Excel, you are still a data analyst. No gatekeeping here. My encouragement is just to broaden your horizons as much as you can.
PS - Getting ready to release my first Youtube short 😱 It’s not much, but I’m getting my feet wet with video content. More to come.
That’s it for this week.
See you next time
Matt ✌️
Whenever you’re ready, there are 2 ways I can help you:
1 | The Data Portfolio Guidebook
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