The Big 3: SQL, Excel, Power BI
The Holy Trinity of Data Analyst Tools
Hey friend,
When people ask me, “What tools do I really need to become a data analyst?” — I always give the same answer:
The Big 3.
SQL. Excel. Power BI.
That’s it.
You can try learning Python. You can explore Tableau or R.
But if you’re starting today and want real skills that help you land freelance gigs, job interviews, and paid work?
These 3 are your bread and butter.
Let me show you why.
📌 Why These 3 (and Not 10 Others)?
Most analysts don’t need to know everything. They just need to know the right things really well.
SQL helps you query data from the source.
Excel helps you clean, slice, and test ideas.
Power BI helps you turn it all into stories with dashboards.
You don’t need 12 certifications.
You need to be dangerous with these 3.
🔍 Skill #1: SQL — Speak the Language of Data
SQL (Structured Query Language) is the real starting point.
📦 Every company stores its data in databases.
🧠 Your job is to extract insights.
⚡ SQL lets you pull, filter, aggregate, and transform data directly.
Top skills to learn:
SELECT,WHERE,GROUP BY,ORDER BYAggregates like
COUNT(),SUM(),AVG()Joins (
INNER,LEFT,RIGHT)Subqueries & Common Table Expressions (CTEs)
Window Functions (think: rolling averages, rankings)
Your first project idea:
Write a query to show the top 5 products by revenue last quarter.
📊 Skill #2: Excel — The OG of Analysis
Excel isn’t dead. It’s just misunderstood.
It’s fast. Flexible. And perfect for exploring raw ideas.
Use it for:
Data cleaning and transformation
Quick KPI calculations
Trend spotting with Pivot Tables
Lookup logic with
VLOOKUP,XLOOKUP,INDEX MATCHBuilding interactive dashboards with slicers and charts
Your first challenge:
Use a dataset of sales and build a Pivot Table that shows monthly revenue by product category.
📈 Skill #3: Power BI — Tell Better Data Stories
Power BI brings your work to life. It’s where data meets decision-making.
Think of it as Excel’s cool cousin — but made for real-time dashboards and executive reports.
What to focus on:
Power Query for data shaping
DAX formulas for custom metrics
Data modeling (relationships, keys, cardinality)
Visuals that match business goals (KPI cards, bar charts, slicers)
Publishing interactive dashboards on the web
Try this mini project:
Connect Power BI to your Excel or SQL data and build a report on customer churn trends.
✅ Your Big 3 Checklist
Ask yourself:
Can I join and filter large tables using SQL?
Can I clean and summarize data in Excel fast?
Do I know how to create a KPI dashboard in Power BI?
Do I understand when to use each tool (and how they complement each other)?
Is at least one of my LinkedIn projects built using SQL/Excel/Power BI?
🔥 Learn by Doing — Not Just Watching
You won’t master these tools by watching tutorials.
You’ll learn when:
Your SQL query breaks and you debug it
Your Excel formula gives a weird result and you figure it out
Your Power BI visual doesn’t show the right trend and you tweak your model
That’s where the learning lives.
📚 Free Resources to Get Started
SQL:
Mode SQL Tutorial
W3Schools SQL Practice
LeetCode SQL Problems
Excel:
ExcelIsFun YouTube
ExcelJet Shortcut Guide
Chandoo.org Examples
Power BI:
Microsoft Learn: Power BI
Guy in a Cube YouTube Channel
SQLBI DAX Guide
🗓️ Suggested 7-Day Sprint
Day 1–2: SQL Foundations + Joins
Day 3–4: Excel for KPIs + Pivot Tables
Day 5–6: Power BI Basics + Visualizations
Day 7: Combine all 3 in one dashboard project
🧠 Reflection Prompt:
Which tool feels most intuitive to me right now?
What’s one metric I can calculate using all 3 tools?
How would I explain the difference between Excel and Power BI to a hiring manager?
Want a complete plan to master SQL, Excel, and Power BI in 60 days?
🎯 Grab the 60-Day Data Analyst Roadmap — trusted by 1,000+ beginners.
You’ll get projects, checklists, and support — all in one place:
🔗 TechLao’s Data Kit
Let’s build the skills that actually get results.
—Randy