# Preparing data in Amazon Quick Sight
<a name="preparing-data"></a>

Datasets store any data preparation you have done on that data, so that you can reuse that prepared data in multiple analyses. Data preparation provides options such as adding calculated fields, applying filters, and changing field names or data types. If you are basing the data source on a SQL database, you can also use data preparation to join tables. Or you can enter a SQL query if you want to work with data from more than a single table.

If you want to transform the data from a data source before using it in Amazon Quick Sight, you can prepare it to suit your needs. You then save this preparation as part of the dataset. 

You can prepare a dataset when you create it, or by editing it later. For more information about creating a new dataset and preparing it, see [Creating datasets](creating-data-sets.md). For more information about opening an existing dataset for data preparation, see [Editing datasets](edit-a-data-set.md).

Use the following topics to learn more about data preparation.

**Topics**
+ [Data Preparation Experience (New)](data-prep-experience-new.md)
+ [Describing data](describing-data.md)
+ [Choosing file upload settings](choosing-file-upload-settings.md)
+ [Data Preparation Experience (Legacy)](data-prep-experience-legacy.md)
+ [Using SQL to customize data](adding-a-SQL-query.md)
+ [Adding geospatial data](geospatial-data-prep.md)
+ [Using unsupported or custom dates](using-unsupported-dates.md)
+ [Adding a unique key to an Amazon Quick Sight dataset](set-unique-key.md)
+ [Integrating Amazon SageMaker AI models with Amazon Quick Sight](sagemaker-integration.md)
+ [Preparing dataset examples](preparing-data-sets.md)