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#dataanalyst

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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.

The data field has a serious naming problem – titles rarely match reality, and it's creating confusion for both companies and careers. If you work with data, I'm curious: does this disconnect resonate with your experience too?

New blogpost:

open.substack.com/pub/datasign

Data Signal · The Great Data Title ConfusionBy Shibaprasad Bhattacharya