🚨 DATA CLEANING IS NOT JUST “REMOVE NULL VALUES”
Real industry data is messy. 😵💫
CRM + Excel + APIs + ERP + databases = data chaos.
A real Data Analyst has to handle:
❌ Missing values
❌ Duplicates
❌ Wrong data types
❌ Inconsistent formats
❌ Outliers
❌ Invalid business values
❌ Messy text & categories
❌ Data quality issues
And the real process is:
RAW DATA → PROFILE → CLEAN → VALIDATE → STANDARDIZE → QUALITY CHECK → TRUSTED DATA → INSIGHTS 📊
Because remember:
Garbage In = Garbage Out.
If you’re learning Data Analytics in 2026, don’t just learn Pandas, SQL & Power BI.
Learn how companies actually deal with dirty data. 🔥
karpathy's CLAUDE.md hit #1 on github trending.
220,000 stars. most devs still haven't read it.
it's 65 lines.
it took AI coding accuracy from 65% to 94%.
the 4 rules inside:
→ think before coding
state your assumptions. ask when unsure. never guess.
→ simplicity first
write the minimum code that solves the problem.
no abstractions nobody asked for.
→ surgical changes
don't touch code unrelated to the request.
every changed line must trace back to what was asked.
→ goal-driven execution
turn vague instructions into verifiable success criteria
before writing a single line.
that's it.
65 lines. 4 rules. 94% accuracy.
save this before everyone else does.