# Data models best practices

When building models, it's always good to follow the commonly accepted best practices in the industry. However, follow them with caution, and do not let them get in the way of getting stuff done.  Here a some best practices that we have identified : 

### Create small  and reusable models

By creating small models, you will ensure that your future self or other users will quickly understand your model structure and output. By creating reusable models, you will ensure that there is also only one source of truth for every data in your company, which will be valuable in the long run

### Follow a naming convention

A lot of efforts can be spared when everything is consistent, and that's also the case in data. Try to use the same naming convention every time it's possible. A naming convention can be applied to you model names, your column names and even in the values that your models output.

### Be explicit

It's always easier to work with data when you don't question yourself about the meaning or the content of a column. For exemple, if your model output a cost in a specific currency and in cents, you should probably name your column `cost_cents_usd`. 

### Document everything

Last but not least, try to document your models by using the description feature in Whaly. 


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