# Model
Every good analysis is not just based on writing SQL, but on understanding how your business relates to the data you capture. The Model/Training space is for the data team to configure:
* Which data should Dot have access to?
* What does each table, column and row represent?
* What are existing analyses that can be build upon?
## Select Data
**Datasource**\
Click on all the tables or explores that Dot will search through.
**Fields**
Select all fields in a datasource that Dot should know about.
## **Describe Data**
You can click suggest to automatically generate documentation and fetch sample values. Make sure to save your changes.
## Define Relationships / Joins
Joining data across different tables is really powerful because it allows us to answer much more broad questions about our business. However, joining data correctly is requires a good understanding of the relationships between your tables.
To ensure Dot avoid join [fan-outs or the chasm trap](https://chat.openai.com/share/790888e3-3ff5-4004-9b58-e04947322757), you can predefine relationships.
For each table, you would specify the foreign key references.
Note:
* a foreign key can be composed key, consisting of multiple columns
* foreign keys should usually refer to primary or natural keys
**Example**
Given the data model above, you want to define 2 Relationships:
* For Orders
* Foreign Key: `user_id`
* Referenced Table: `Users`
* Referenced Keys: `id`
* For OrderItems
* Foreign Key: `order_id`
* Referenced Table: `Orders`
* Referenced Keys: `id`
