> For the complete documentation index, see [llms.txt](https://dots.gitbook.io/dots-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://dots.gitbook.io/dots-docs/project-prep/data-preparation.md). # Data Preparation At **Dots**, we offer multiple fields designed to help you map your data in the best possible way, making your analysis smoother. You can simply upload your Excel sheet, and the platform will automatically map your data to the right field. However, to achieve the most accurate results, we recommend preparing your Excel file in advance. Define which column aligns with which field and enter your data accordingly. To guide you, the table below shows how to structure your data for each field type. You can also refer to the [sample sheet](https://docs.google.com/spreadsheets/d/1GJhuCk1vKN-TovbLI1pgh9SB61CahF9g0JqUAsKMQRQ/edit?usp=sharing) over here to test with sample data.

Component	Description
Text	Text field is designed for entering brief text, usually between 10 and 20 words. It is best suited for short responses, which assist in data analysis using the AI categorization feature.
Rich Text Editor	Rich Text Editor allows adding large texts, such as transcripts and summaries. This component is used when qualitative data needs to be highlighted using tags and used for future analysis.
Numbers	Number is for any numeric data. It will be calculated in relevant ranges.
URL	URL can be used when you need to include any external or reference link in your data.
Single Select	Single select helps you with selecting a input a single option.
Multiple Select	Multiple select is a field type where you can input multiple options using a separator in between them.
Single Tag	Single tag is a field type where you can input a single tag. Tags help organize, filter, and connect data across datasets.
Multiple Tag	Multiple tag is a field where you can input multiple tag options using a separator in between them. Tags helps organize, filter, and connect data across datasets.

### Kobo to Dots So you’ve exported your dataset from KOBO and now you want to get it ready to upload into **Dots**. Here’s how you can clean things up in a way that’s easy to follow. 1. **Export Your KOBO Data** * First, head into KOBO and download your dataset as an **.xlsx file**. 2. **Remove Extra Fields** * Take a look at your columns — some of them are just KOBO metadata you won’t need in Dots. * Go ahead and delete any columns that aren’t actually needed for your upload. 3. **Find the Multi-Select Columns** * KOBO exports multi-select questions by creating a separate column for each option.\ For example: **Main crops grown last year/Sunflower, Main crops grown last year/Pigeonpea**

4. **Combine Options into One Column** * In Dots, you don’t need a separate column for every option. * Instead, **combine the selected options into one field** using a delimiter like `;` or `,`. * So if someone picked Rice, Paddy and Soybean, your combined value should look like:\ Rice\&Paddy\&Soybean

5. **Clean Up the Extra Columns** * Once you’ve moved all multi-select values into your single field, you can delete those individual option columns. 6. **Quick Quality Check** * Give your sheet a quick scan: * Are all combined values using the same delimiter? * Any empty values to clean? * Everything spelled consistently? 7. **Save It** * Save your cleaned .xlsx — this version is now ready to upload into Dots!