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Without normalising your data, you are effectively using an excel spreadsheet-esque design to store all of your data contiguously.

This introduces update / delete / insert user errors a critical design flaw, in that if say, an order needed an item adding / deleting / updating then all data tied to that order must be altered as well.

You will also generate a great deal of redundant data, which can consume space rapidly in a large database. In the above example you would have to repeat all the order and customer details for every item on each line over and over.

Data in a flat format will also be highly difficult to query for statistics, in part due to the layout of the data itself and in part because of user error, for example if you wanted to count the number of times your polish customer had placed an order (Mr Zbigniew Dmartchyzk), in a flat database your 100 data in-putters are probably going to fail at spelling that correctly every time, so you could end up with a hundred or so different spellings and no method of querying the data correctly.

If you start to separate the data into separate tables in any way, you have already begun the process of normalisation.

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12y ago
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16y ago

Normalization is needed in data modeling of any system because it helps to remove the following anomalies:

* Insert * Delete * Update There are 5 steps to normalize the database. Other details can be achieved via Google search. isn't it?

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