SQL Duplicate Data: Why DISTINCT Is NOT the Fix | Real-World SQL
Have duplicate-looking rows in SQL? Be careful — not every repeated row is a true duplicate.
In this real-world SQL masterclass, we investigate duplicate data the way a senior data analyst or SQL developer should: by defining the grain, identifying the business key, checking lineage, and proving whether the issue comes from bad data, a bad JOIN, or repeated file loads.
This video goes beyond “just use DISTINCT.”
You’ll learn why DISTINCT often hides the symptom instead of fixing the cause — and when techniques like ROW_NUMBER() are more appropriate.
In this video, you’ll learn:
How to tell the difference between true duplicate data and valid repeated rows
Why bad JOINs can create duplicate-looking results
Why DISTINCT is not a long-term fix
How to use ROW_NUMBER() when a survivor rule is required
How file hashes and idempotency help detect repeated loads
How to think about prevention controls in real production systems
Topics covered:
Stored duplicates vs valid repeats
Bad JOIN vs bad data
DISTINCT vs ROW_NUMBER()
Duplicate file detection with FileHash
Near-duplicate review and prevention controls
Real-world SSMS demos
If you are learning SQL for real-world analytics, reporting, healthcare data, ETL, or interview preparation, this lesson will help you debug duplicate data correctly.
Playlist: SQL Interview & Real-World Query Masterclass
Channel: Data With Srini Voleti
#SQL #SQLServer #DataAnalytics #SSMS #TSQL #SQLTutorial #RealWorldSQL #DataAnalyst #ROW_NUMBER #distinctwheels
00:00 Introduction — Why DISTINCT Is Not the Fix
04:11 Demo 1 — Stored Duplicates vs Valid Repeats
05:57 Demo 2 — Bad JOIN vs Bad Data
07:29 Demo 3 — DISTINCT vs ROW_NUMBER()
09:26 Demo 4 — Duplicate FileHash & Idempotency
10:53 Demo 5 — Near Duplicates & Prevention
12:42 Production-Safe Cleanup & Senior SQL Approach
16:10 Final Takeaways