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Why normalize databases?
Yesterday, my tutoring student asked me why databases need to be normalized at all. She said: “Wouldn’t it be easier to just have one big table with all the information?”

It’s a common first question when learning about relational databases.
At first, one big table (e.g. customer name, order date, product name, price) seems easiest.

I told her:
:blobcoffee: Because that quickly leads to data redundancy, anomalies, and integrity issues when inserting, updating, or deleting records.
:blobcoffee: Normalization means structuring data into separate, related tables, so that each fact is stored only once. This reduces redundancy & preserves consistency.

Can you remember learning to walk as a baby? You didn’t read a manual. Neither does an AI agent.

Reinforcement Learning (RL) isn’t about knowing the correct answer.
It’s about learning through trial and error, by interacting with an environment & receiving feedback.

That’s how AlphaGo defeated a world champion:
It first learned from expert games. Then it played against itself, millions of times, using RL to get better with each game. That’s how it mastered Go.