I’ll be honest, when I first heard “Excel for data analysis,” I mentally filed it under things I already know. I’ve spent a few years in tech, pre-sales, project management, and vendor partnerships, and I figured Excel was just spreadsheets with a few formulas. I was wrong.
This week in my Data Science & Analytics course at LuxDev HQ, we worked on an HR dataset. And it was messy. Missing hire dates, duplicate employees, an age listed as 99 and someone’s project count written as “ten” instead of 10. Real data. Real chaos.
Working through that dataset taught me more about data than any definition ever could. Here’s what I’ve learned about how Excel is really used in practice.
But first, what is Excel?
Excel is a spreadsheet tool from Microsoft for storing, organising, and analysing data in rows and columns. Think of it as a super-powered table one where you can run calculations, spot patterns, and clean up messy information, all in one place.
3 Ways Excel Shows Up in the Real World
HR & People Data Management
HR teams use Excel to track headcount, flag performance gaps, and plan promotions. Our dataset spanned 80+ employees, multiple departments, and locations from Nairobi to New York. Excel is what kept the chaos in check and made the analysis possible
Financial Reporting & Payroll
Before any payroll report goes out, someone has to total the right figures, check for missing entries, and make sure everything adds up. That work happens in Excel, using the exact formulas we practiced in class.
Business Decision-Making
When a manager asks “How many permanent staff are in Nairobi?” or “What’s the total bonus payout for Sales?”—those are business questions that Excel answers in seconds, with the right formula.
3 Excel Features I Learned This Week
Conditional Formatting
This highlights cells automatically based on rules you set. I used it to spot outliers—an age of 99, a last promotion year of 1900, and a bonus with a currency symbol. Instead of scanning hundreds of rows, Excel flagged the problems instantly.
ROUND, ROUNDUP
These functions turn rough numbers into professional reporting
SUMIF, SUMIFS, COUNTBLANK, COUNTIF, COUNTIFS — Aggregate Functions with Conditions
This is where Excel starts to feel like actual analysis. These functions let you ask specific questions of your data, not just “what’s the total” but “what’s the total for this specific group, under these specific conditions.”
COUNTBLANK** This counts every empty cell, so before I even started cleaning, I knew exactly how many gaps I was dealing with.
COUNTIF lets me count how many employees belonged to each department, or how many had a performance score of 8 or above. One formula, one condition.
COUNTIFS** took it further, two or more conditions at once. How many employees are Interns, female, above 40 yrs AND based in Nairobi? How many are in IT AND fully remote?
SUMIF gave me the total bonus paid out to the Sales department. =SUMIF(D:D, "Sales", K: K) that’s it. One formula.
SUMIFS added another layer, total bonuses for Permanent staff in the Sales department only. Multiple columns, multiple conditions, one clean result. This is what financial summaries are actually built from.
How This Week Changed the Way I See Data
Before this week, I saw data as something you simply report. Now, I realize data is something you interrogate, challenge, and understand before you trust it. Every inconsistency is a clue to a human story or a broken process. It’s the analyst’s job to find, fix, and ensure the data is trustworthy before anyone makes a decision based on it.
If you’re just getting into data analytics, start with Excel. It will teach you how to think about data long before you write your first line of code.
Top comments (1)
Excellent article. It is practical, relatable, and clearly connects Excel to real-world HR data cleaning, formulas, reporting, and decision-making.