If you're starting your journey into data analytics, one of the first questions you’ll face is:
Should I learn Excel or SQL first?
Both are essential tools in a data analyst’s toolbox — but they serve different purposes. In this guide, we’ll break down the differences between Excel and SQL, when to use each, and which one is best to start with in 2025.
What Is Excel?
Microsoft Excel is a spreadsheet application used for organizing, analyzing, and visualizing data. It’s been a staple in business environments for decades and remains one of the most accessible tools for beginners.
Common Excel Features Used in Data Analytics:
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Sorting and filtering data
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Creating pivot tables
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Using formulas (SUM, IF, VLOOKUP, etc.)
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Basic charts and graphs
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Data cleaning using built-in functions
What Is SQL?
SQL (Structured Query Language) is a programming language used to interact with databases. It allows analysts to pull, filter, and join large datasets directly from relational databases.
Common SQL Operations in Data Analytics:
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Querying data with
SELECT -
Filtering with
WHERE -
Combining tables with
JOIN -
Aggregating data with
GROUP BY -
Sorting and limiting data with
ORDER BYandLIMIT
Excel vs SQL: Head-to-Head Comparison
| Feature | Excel | SQL |
|---|---|---|
| Ease of Use | Very beginner-friendly | Slight learning curve |
| Best For | Small datasets, quick summaries, visual analysis | Large datasets, data extraction, performance |
| Data Size Limit | Slower with large data (over 1 million rows) | Handles millions of rows efficiently |
| Data Cleaning | Manual, but visual | Code-based, scalable |
| Learning Curve | Easier for non-tech users | Requires learning syntax |
| Visualizations | Built-in charts and graphs | Needs external tools (like Power BI/Tableau) |
Which One Should You Learn First?
✅ Start with Excel if:
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You’re completely new to data analysis
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You prefer a visual interface
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You want to quickly start working with small datasets
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You're applying for business analyst or entry-level roles
✅ Start with SQL if:
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You’re comfortable with basic tech or code
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You want to work with databases and big data
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You're aiming for roles like data analyst, BI analyst, or data engineer
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Your job involves working with backend systems or raw data sources
Ideal Learning Path in 2025
Here’s a recommended order to get the best of both worlds:
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Excel – Learn the basics of data handling, cleaning, and pivot tables.
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SQL – Once you're comfortable with data structures, dive into SQL for scalable, automated querying.
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Power BI or Tableau – Learn to visualize insights from both Excel and SQL data.
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Python or R (Optional) – For advanced data analysis and automation.
Final Thoughts
Excel and SQL are not rivals — they’re partners.
Start with Excel if you’re a complete beginner, then move to SQL as your data becomes bigger and your needs become more complex. In 2025, companies still rely on both tools heavily, so knowing both gives you a big edge in the job market.
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