> For the complete documentation index, see [llms.txt](https://daton-sarasanalytics.gitbook.io/daton/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://daton-sarasanalytics.gitbook.io/daton/integrations/data-sources/files/email-attachments/about-email-attachments-connector.md). # About Email Attachments Connector The Email Attachment Connector in Daton offers a solution to automate the extraction, parsing, and uploading of CSV files from emails. The Email Attachment Connector is a powerful feature within Daton that simplifies the process of saving CSV files to your chosen destination. This connector streamlines the extraction of one or more attachments from incoming emails, parses the data contained within these attachments, and seamlessly uploads it to your specified destination. **Key Functions and Benefits:** * **Attachment Extraction:** With the Email Attachment Connector, you can effortlessly extract attachments from emails, saving you the manual effort of downloading and handling each attachment separately. * **Data Parsing:** This connector is designed to intelligently parse the data within the attachments, ensuring that the information is accurately structured and ready for integration. * **Automated Upload:** Once the data is extracted and parsed, the Email Attachment Connector automates the process of uploading the CSV files to your destination, eliminating the need for manual data transfer. **Streamlined Data Flow:** By integrating the Email Attachment Connector into your workflow, you can streamline your data management process. It offers a seamless and efficient way to handle email attachments, making the data within them easily accessible and ready for analysis or storage. This documentation provides comprehensive guidance on effectively utilizing the Email Attachment Connector to streamline your data management processes. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://daton-sarasanalytics.gitbook.io/daton/integrations/data-sources/files/email-attachments/about-email-attachments-connector.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `build a script that syncs our docs to a CMS` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.