Data Analyst for Beginners in 30 Days: Day 4: Excel Fundamentals for Analysts

 

Introduction

Welcome to Day 4! Today is where data starts to feel powerful. You’ll learn how analysts use Excel to turn raw rows into clear, meaningful numbers that support business decisions. Don’t worry—this is beginner-friendly and hands-on.

By the end of today, you’ll be comfortable opening a dataset, applying core formulas, and building a simple metrics table like a real analyst

What You’ll Learn Today

1️⃣ Core Excel Formulas (The Analyst Essentials)

We’ll focus on three formulas you’ll use every single day as an analyst:

🔢 SUM

• What it does: Adds numbers together

• Why analysts use it: Total sales, total revenue, total units sold

Example:

=SUM(B2:B101) → Adds all sales values

AVERAGE

• What it does: Finds the mean value

• Why analysts use it: Average order value, average daily sales

Example:

=AVERAGE(B2:B101)




COUNT

• What it does: Counts cells with numbers

• Why analysts use it: Number of transactions, number of records

Example:

=COUNT(A2:A101)

💡 Analyst tip: COUNT only counts numbers, not text. 




Dataset: Sales Transactions (CSV)

You’ll work with a simple Sales Transactions CSV, typically containing:

• Date

• Order ID

• Product

• Quantity

• Sales Amount

This mirrors real business data you’d get from finance, e-commerce, or operations teams.

Hands-On Exercise: Create a Basic Metrics Table

🧪 Exercise Instructions

1. Open the Sales Transactions CSV in Excel

2. Create a new sheet called Metrics

3. Build this table:

✅ Expected Output

A clean metrics table that answers:

• How much did we sell?

• What’s the average sale?

• How many transactions happened?

This is exactly how analysts start reports.

What to Expect After Completion of Day 4

After finishing Day 4, you will be able to:

• Confidently navigate Excel like an analyst

• Apply core formulas to real datasets

• Create simple KPI and metrics tables

• Understand how raw data becomes business insight

• Be ready for Day 5: Data Cleaning & Data Quality

This is a huge milestone—Excel is a non-negotiable skill for analysts

Common Beginner Mistakes (Avoid These!)

• Using text cells in SUM or AVERAGE

• Forgetting to lock ranges when copying formulas

• Mixing raw data and metrics in the same sheet

You’re already ahead by learning this early

Conclusion

Excel is the foundation tool of data analysis, and today you’ve taken your first real analyst step. These formulas may look simple—but they power dashboards, reports, and executive decisions every day.

Mastering this means you’re officially thinking like an analyst


Next Lesson:

Data Analyst for Beginners in 30 Days: Day 5: Excel Lookups and Logic
https://www.wisemoneyai.com/2026/01/data-analyst-for-beginners-in-30-days_24.html