Data normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It's like Marie Kondo for your database - you're tidying up and organizing your data so it's not a cluttered mess and you can actually find what you need without wanting to flip a table.

How to use it in a sentence

• I spent all weekend data normalizing my new database schema instead of playing Elden Ring like a normal person. I really need to rethink my life choices.

• My boss asked me to "quickly" data normalize our 20-year-old legacy database with no documentation. I told him I'd get right on it, right after I finish my other project of boiling the ocean.

If you actually want to learn more...

• A Simple Guide to Five Normal Forms in Relational Database Theory - A nice overview of the different normal forms and how to achieve them. It's like a cheat sheet for data normalization.

• Data Normalization in SQL - A more in-depth look at data normalization concepts and how to implement them in SQL. Perfect for when you really want to get your hands dirty with some data normalization action.

• When Not to Normalize your SQL Database - Because sometimes data normalization isn't always the answer. This article covers some scenarios where you might want to denormalize for performance reasons. It's like the "break glass in case of emergency" of data normalization.

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