Before starting this project, I honestly knew almost nothing about Excel. I had heard about it, seen people use it, but I never really understood how powerful it is. As just a girl trying to figure things out, I was honestly a bit nervous and overwhelmed at first. But at the same time, I was open to learning and ready to take on the challenge. Like many beginners, I saw it as just a tool for storing data in rows and columns. However, through hands-on practice, I quickly realized that Excel is far more powerful—it is a complete data analysis tool used by professionals across industries.
This article shares how Excel is applied in real-world data analysis, based on my experience building a product performance dashboard.
What is Excel?
Microsoft Excel is a tool used to organize, clean, analyze, and present data. It works using rows and columns, and it has features like formulas, PivotTables, charts, and slicers that help turn raw data into meaningful information. Even in 2026, Excel remains one of the most widely used tools for data analysis due to its accessibility and versatility
At first, it looked complicated—but as I started using it, I slowly began to understand how everything connects.
🌍 Real-World Use
I learned that Excel is used almost everywhere—in business, marketing, finance, and even e-commerce. For example, a company like Jumia can use Excel to analyze:
- Product prices
- Discounts
- Customer reviews
- Ratings
This helps them make decisions like:
Which products to promote
Whether to increase or reduce prices
Which products need improvement
Seeing this made me realise that Excel is not just about numbers—it actually helps businesses grow.
🛠️ What I Learned (As a Beginner)
Even though I started from zero, I managed to learn and use several important Excel tools:
🔹 Data Cleaning
This was one of the hardest parts at first, but also the most important.
I used:
Text to Columns
Find & Replace
Functions like LEFT(), VALUE(), and ABS()
This helped me:
Remove “KSh” and commas
Convert text into numbers
Fix negative review values
Extract ratings from text
🔹 Data Enrichment
I created new columns using formulas:
Discount Amount
Rating Category (Poor, Average, Excellent)
Discount Category (Low, Medium, High)
At first, formulas looked scary—but once I understood them, they became really useful.
🔹 PivotTables
This was honestly one of the most powerful tools I learned. It made analyzing data much faster and easier.
I used PivotTables to:
Find averages
Identify top products
Group data into categories
🔹 Charts & Visuals
I created:
Bar charts for top products
Donut charts for categories
Scatter plots to see relationships
This is where everything started to make sense visually.
🔹 Slicers & Interactivity
This part felt really cool 😄
I added slicers so the dashboard can filter data instantly.
It made everything interactive and more professional.
🔹 Conditional Formatting
I used colors to highlight:
High discounts (green)
Low ratings (red)
This made important insights easy to spot.
💡 Personal Reflection
This experience completely changed how I see data.
At the beginning, I was confused and honestly a bit stressed because everything felt new. But as I kept practicing, I started understanding patterns and relationships.
Now I can look at data and think:
Why is this happening?
What does this mean?
What decision can be made from this?
For example, I noticed that:
Medium discounts sometimes have better ratings
High discounts don’t always mean more reviews
That really surprised me.
I’m still a beginner, and I know I have a lot to learn but now I feel more confident. This is just the start of my journey into data analysis, and I’m excited to keep improving.
Top comments (0)