Scrapy provides two ways to handle structured data: Item and Item Loader. Item is a simple container for storing extracted data, similar to a dictionary but with additional features such as field validation and default values. Items need to be defined in the items.py file, using the Field class to define fields. Item Loader is a more advanced tool that provides a convenient way to populate Item objects. Item Loader supports input processors and output processors, which can process data before and after it is populated into the Item. Input processors are used to process raw data extracted from web pages, while output processors are used to process data that is ultimately stored in the Item. Item Loader also supports chaining, allowing data to be processed step by step. Using Item Loader can simplify data processing logic and make code clearer and more maintainable. Developers can choose to use Item or Item Loader based on project requirements, or combine both.