To be honest, when I signed up for a Data Science and Analytics course, it hadn't crossed my mind that Excel was the very first tool I would start with. I figured we'd jump straight into dashboards, maybe some Python, something that felt more "data sciency". But here we are, Week 1, deep in spreadsheets.
And the best part about this is that I'm actually glad it started here.
So, what is Excel?
Excel is a spreadsheet tool by Microsoft. You work with data in rows and columns, run calculations, sort things, filter things and build reports. Sounds simple, right? But once you start using it on real data, you realize it's literally the backbone of a huge chunk of the business world.
Ways Excel shows up in real work
- Financial Reporting - Accountants and finance teams use Excel to track income, expenses, budgets and forecasts. Every month, someone somewhere is pulling together a financial report in Excel before it ever reaches a boardroom.
- Sales and Business Performance - Sales teams track numbers in Excel — who sold what, which region is hitting targets, which product is underperforming. It's the first place most managers go when they want to understand their numbers.
- Marketing Analysis - Marketers use Excel to measure campaigns, click rates, conversions and customer behavior over time. Before any fancy BI tool, most marketing teams have a spreadsheet tracking what's working.
Features I used this week
Before jumping into formulas, the first thing I had to do was just understand how Excel is laid out. It sounds obvious but getting comfortable with the interface first made everything else easier.
Once I had that down, I started working with these features:
- Sorting - Organizing data by numbers, text or dates. Useful when you need to quickly rank results or find the highest/lowest values.
- Filtering - Showing only the rows that match a certain condition. Instead of scrolling through hundreds of entries, you just filter and focus on what matters.
- Data Validation - This one is about keeping data clean at the entry point. You can set rules so that only certain values are accepted in a column. It stops messy, inconsistent data before it becomes a problem.
- Freeze Panes - When you're scrolling through a big dataset, your headers disappear off the top of the screen. Freeze Panes keeps them visible no matter how far down you scroll. Simple but incredibly useful.
Functions I Learned
SUM, AVERAGE and COUNT - These feel basic but they're everywhere. I used SUM to total a column of sales figures, AVERAGE to find a mean score and COUNT to quickly see how many entries were in a dataset.
COUNTIF - This was my favourite this week. Instead of manually counting how many times something appears, COUNTIF does it automatically based on a condition. I used it to count how many entries matched a specific category. Such a small thing that makes a big difference.
SUMIF and SUMIFS - Add values that meet one or more conditions.
AVERAGEIF and AVERAGEIFS - Calculate averages based on selected conditions.
These are the functions that help you answer actual business questions - total sales by product, customer count by region, average performance across departments.
Text and Date Functions - I also got introduced to LEFT(), RIGHT(), LEN(), and CONCAT() for working with text, and TODAY(), NOW(), DAY(), MONTH(), YEAR() for dates. These are used a lot in data cleaning — pulling out parts of a string, combining columns, or breaking a date into components you can analyze separately.
💡How this changed the way I see data
Before this week, I looked at a spreadsheet and just saw a table. Now I see questions. What's the total? What's the average? What's pulling the numbers up or down? Excel didn't just teach me formulas, it taught me to ask better questions about data.
I'm only in Week 1 and I already feel like I'm thinking differently. That's quite the leap.
If you're also starting out in data analytics, don't skip Excel thinking it's too basic. It's the foundation everything else is built on.
💬 Are you also learning data analytics or just getting started with Excel? Drop a comment - I'd love to connect with others on the same path.
