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Why Excel Matters (And Pitfalls to Consider)
Pro's and con's to this ever popular data tool
Hey everyone š
Letās talk about Excel.
Itās quite a polarizing tool. Some love it. Some hate it. And itās been the butt of many a data joke.
Donāt 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?
Itās still a staple tool for so many businesses. Let me humor you with one more memeā¦
All roads really do lead back to Excel at some point.
So itās 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 Iād like to explain some key reasons why you should invest time in getting good with Excel.
But Iād 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 | Itās 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 theyāve 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. Itās 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 | Itās not going anywhere
Excel is the most widely used data tool, and itās used for literally everything. As the memes above suggest, itās carrying a lot of weight worldwide. And when youāve seen what Iāve seen behind the veil of some companies, you know that itās 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 theyāve exceeded its limits. Iāve witnessed this firsthand but friends of mine who are consultants see it all the time too.
Itās easy to get comfortable with Excel and a lot of companies hang on to it because itās what they know, even if itās no longer the best tool for the job.
2 | Itās powerfulā¦.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 canāt hold that much data and it starts crashing once it begins reaching its threshold.
When you think about it, itās 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 | Itās easy to hide behind
This one might sting a little, but itās 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 donāt 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, itās 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 š± Itās not much, but Iām getting my feet wet with video content. More to come.
Thatās it for this week.
See you next time
Matt āļø
Whenever youāre ready, there are 2 ways I can help you:
1 | The Data Portfolio Guidebook
If youāre looking to create a data portfolio but arenāt sure where to start, Iād recommend this ebook: Learn how to think like an analyst, develop a portfolio and LinkedIn profile, and tackle the job hunt.
2 | 1:1 Coaching Call
For help navigating the data job hunt, consider booking a 1:1 career guidance session with me. There are a few options available to help you get to your ideal data job faster.