Top Programming Languages for Data Analysts in 2025
Introduction
Top 5 Programming Languages for Data Analysts (2025 Ranking)? Programming is the backbone of data analytics. While tools like Excel and Tableau help visualize data, coding languages unlock advanced analysis, automation, and scalability.
In 2024, these 5 programming languages are essential for data analysts:
- SQL (Database Querying)
- Python (General-Purpose Analytics)
- R (Statistical Modeling)
- Power BI DAX (Business Intelligence)
- SAS (Enterprise Analytics)
Let’s compare their use cases, pros/cons, and learning resources—including Faisal Sir’s Data Analytics Program for hands-on training.
1. SQL (Structured Query Language)
Why Learn?
- Used in 90%+ of data jobs (LinkedIn 2024 Report)
- Extracts data from databases (MySQL, PostgreSQL)
Key Features:
✔ SELECT, JOIN, GROUP BY queries
✔ Fast for large datasets
✔ Easy to learn basics
Example Query:
SELECT customer_name, SUM(sales) FROM orders GROUP BY customer_name ORDER BY SUM(sales) DESC;
Learning Resources:
- Faisal Sir’s SQL Guide (Free tutorials)
- Mode Analytics SQL Tutorial
2. Python
Why Learn?
- #1 language for data science (IEEE Spectrum 2024)
- Libraries: Pandas (data cleaning), NumPy (math), Matplotlib (visualization)
Key Features:
✔ Versatile (web scraping, ML, automation)
✔ Large community support
Example Code (Pandas):
import pandas as pd
df = pd.read_csv(“sales.csv”)
print(df.groupby(“region”)[“revenue”].mean())
Learning Resources:
3. R
Why Learn?
- Dominates academic research and statistics
- Strong in data visualization (ggplot2)
Key Features:
✔ Built for statistical analysis
✔ 15,000+ packages (e.g., dplyr, tidyr)
Example (Linear Regression):
model <- lm(sales ~ advertising, data=df) summary(model)
Learning Resources:
4. Power BI DAX
Why Learn?
- Essential for Power BI dashboards
- Used by 75% of Fortune 500 companies
Key Features:
✔ Business-friendly formulas
✔ Integrates with Excel/SQL
Learning Resources:
5. SAS
Why Learn?
- Still used in healthcare, banking, and government
- High-paying niche roles
Key Features:
✔ Enterprise-grade security
✔ Strong in clinical trials analysis
Learning Resources:
Comparison Table
| Language | Best For | Difficulty | Avg. Salary (US) |
|---|---|---|---|
| SQL | Database queries | Easy | $85,000 |
| Python | Machine learning, automation | Medium | $110,000 |
| R | Statistics, research | Medium | $95,000 |
| DAX | Power BI reports | Easy | $90,000 |
| SAS | Enterprise analytics | Hard | $105,000 |
Which Language Should You Learn First?
- Beginners: Start with SQL → Python
- Business Analysts: SQL + DAX
- Researchers: R or Python
Pro Tip: Enroll in Faisal Sir’s Data Analytics Program to master all 5 languages with real projects.
FAQ
Q: Is Python better than R for jobs?
✅ Python has 3x more job postings (Indeed 2024), but R is preferred in biostatistics.
Q: Can I skip SAS?
⚠️ Yes, unless you target healthcare/banking. Most companies use Python/SQL.
Next Steps
- Practice SQL on StrataScratch
- Build a Python project with Kaggle Datasets
- Join Faisal Sir’s Program for mentorship
