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📊 I Built an interactive Customer Behaviour Analysis Dashboard to explore customer patterns, revenue trends, and purchasing behavior using real business KPIs.
Turning raw data into actionable insights is what I do as a Data Analyst.
🛠 Tools used
Excel for data preparation
Power BI for visualization and storytelling
This project shows how data reveals powerful business insights when analyzed properly
Data Analyst, hear me out, look at that No 13 in this image, yes, it’s a supply chain role but I’m assured every Supply chain manager will be eager to have you man that position, when I was consulting for Google, I did recommended one of my boys who’s a badass Data guy for a
The best engineers I know delete more code than they write
Junior engineers add features. Senior engineers remove complexity
Every line of code you write is a liability. It needs to be maintained. It can break. It adds cognitive load to anyone who reads it later
The best pull requests I've seen in the last year? Half of them deleted more than they added. Someone refactored three classes into one. Someone replaced 200 lines of custom logic with a library function. Someone removed an entire abstraction layer that wasn't pulling its weight
Deletion is a skill. You have to know what's safe to remove. You have to understand the system well enough to see what's redundant, over-engineered, or just wrong
Next time you open a file, ask: what can I remove?
The best code is the code you don't write
Free Certification Courses to Learn Data Analytics in 2025:
1. Python
🔗 https://t.co/dIF8TuaOLu
2. SQL
🔗 https://t.co/Ge4bFjars9
3. Statistics and R
🔗 https://t.co/41ya4HlxPS
4. Data Science: R Basics
🔗https://t.co/56xixoYoMg
5. Excel and PowerBI
🔗 https://t.co/oWULVWbQPg
6. Data Science: Visualization
🔗https://t.co/eQ7buwP4QU
7. Data Science: Machine Learning
🔗https://t.co/RYTIF3cocp
8. R
🔗https://t.co/aPvThGhFHw
9. Tableau
🔗https://t.co/94KUoem3Bf
10. PowerBI
🔗 https://t.co/gOV6kIG2kQ
11. Data Science: Productivity Tools
🔗 https://t.co/0fvxcgIQ4W
12. Data Science: Probability
🔗https://t.co/J0eC5jlOGX
13. Mathematics
🔗https://t.co/b62getHyo7
14. Statistics
🔗 https://t.co/Y82ToFqsFs
15. Data Visualization
🔗https://t.co/Yz8e2T6mdn
16. Machine Learning
🔗 https://t.co/VoHcNGJvfC
17. Deep Learning
🔗 https://t.co/TY3cjGHXdK
18. Data Science: Linear Regression
🔗https://t.co/5N2UOWUgxw
19. Data Science: Wrangling
🔗https://t.co/zTsUAAn1hE
20. Linear Algebra
🔗 https://t.co/UPNbNapSf0
21. Probability
🔗 https://t.co/UdOPPPyYJ8
22. Introduction to Linear Models and Matrix Algebra
🔗https://t.co/3hOAvinvhe
23. Data Science: Capstone
🔗 https://t.co/ac8w6CLS9T
24. Data Analysis
🔗 https://t.co/tKh5FYjMRM
25. IBM Data Science Professional Certificate
https://t.co/gFsFS3B6zu
26. Neural Networks and Deep Learning
https://t.co/SPyU710NvG
27. Supervised Machine Learning: Regression and Classification
https://t.co/ATOsYimRAJ
Dear Data Analyst!
3 months of focused and consistent LEARNING can get you a job.
“Oct-Nov-Dec”
- Focus on the right tools
- Focus on the right materials
- Learn from others
- Build projects
- Network
Don’t complicate it.