Normalization vs Denormalization

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What is Normalization vs Denormalization?

Database normalization is a process used to organize a database into tables and columns. The idea is that a table should be about a specific topic and that only those columns which support that topic are included. This limits the number of duplicate data contained within your database. This makes the database more flexible by eliminating issues stemming from database modifications.

Denormalization is the opposite of normalization. It is the process of adding redundant data to a database to improve read performance. This is done by adding duplicate data into multiple tables to avoid expensive joins. This is done at the expense of increased storage and decreased write performance.

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Normalization vs Denormalization: common questions

Can I learn Normalization vs Denormalization in Hindi?

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Is this Normalization vs Denormalization tutorial for beginners?

It is lesson 177 of 200 in the free BI Analyst roadmap, in stage 49, Normalization vs Denormalization. If you are new to BI Analyst, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.

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