add clarifying info on how MF joins works

website/docs/docs/build/join-logic.md

@@ -10,24 +10,28 @@ Joins are a powerful part of MetricFlow and simplify the process of making all v
 
 Joins use `entities` defined in your semantic model configs as the join keys between tables. Assuming entities are defined in the semantic model, MetricFlow creates a graph using the semantic models as nodes and the join paths as edges to perform joins automatically. MetricFlow chooses the appropriate join type and avoids fan-out or chasm joins with other tables based on the entity types.
 
-<details>
-  <summary>What are fan-out or chasm joins?</summary>
-  <div>
-    <div>&mdash; Fan-out joins are when one row in a table is joined to multiple rows in another table, resulting in more output rows than input rows.<br /><br />
-    &mdash; Chasm joins are when two tables have a many-to-many relationship through an intermediate table, and the join results in duplicate or missing data. </div>
-  </div>
-</details>
-
+<Expandable alt_header="What are fan-out or chasm joins?" >
+-  Fan-out joins are when one row in a table is joined to multiple rows in another table, resulting in more output rows than input rows.
+-  Chasm joins are when two tables have a many-to-many relationship through an intermediate table, and the join results in duplicate or missing data.
+</Expandable>
 
 ## Types of joins
 
 :::tip Joins are auto-generated
 MetricFlow automatically generates the necessary joins to the defined semantic objects, eliminating the need for you to create new semantic models or configuration files.
 
-This document explains the different types of joins that can be used with entities and how to query them using the CLI.
+This section explains the different types of joins that can be used with entities and how to query them.
 :::
 
-MetricFlow primarily uses left joins for joins, and restricts the use of fan-out and chasm joins. Refer to the table below to identify which joins are or aren't allowed based on specific entity types to prevent the creation of risky joins.
+Metricflow uses these specific join strategies:
+
+- Primarily uses left joins when joining `fct` and `dim` models. Left joins make sure all rows from the "base" table are retained, while matching rows are included from the joined table.
+- For queries that involve multiple `fct` models, MetricFlow uses full outer joins to ensure all data points are captured, even when some `dim` or `fct` models are missing in certain tables. 
+- MetricFlow restricts the use of fan-out and chasm joins. 
+
+Refer to [SQL examples](#sql-examples) for more information on how MetricFlow handles joins in practice.
+
+The following table identifies which joins are allowed based on specific entity types to prevent the creation of risky joins. This table primarily represents left joins unless otherwise specified. For scenarios involving multiple `fct` models, MetricFlow uses full outer joins.
 
 | entity type - Table A | entity type - Table B | Join type            |
 |---------------------------|---------------------------|----------------------|
@@ -39,9 +43,19 @@ MetricFlow primarily uses left joins for joins, and restricts the use of fan-out
 | Unique                    | Foreign                   | ❌ Fan-out (Not allowed) |
 | Foreign                   | Primary                   | ✅ Left                 |
 | Foreign                   | Unique                    | ✅ Left                 |
-| Foreign                   | Foreign                   | ❌ Fan-out (Not allowed) |   
+| Foreign                   | Foreign                   | ❌ Fan-out (Not allowed) |
+
+### Semantic validation
 
-### Example
+MetricFlow performs semantic validation by executing `explain` queries in the data platform to ensure that the generated SQL gets executed without errors. This validation includes:
+
+- Verifying that all referenced tables and columns exist.
+- Ensuring the data platform supports SQL functions, such as `date_diff(x, y)`.
+- Checking for ambiguous joins or paths in multi-hop joins.
+
+If validation fails, MetricFlow surfaces errors for users to address before executing the query.
+
+## Example
 
 The following example uses two semantic models with a common entity and shows a MetricFlow query that requires a join between the two semantic models. The two semantic models are:
 - `transactions`
@@ -83,6 +97,50 @@ dbt sl query --metrics average_purchase_price --group-by metric_time,user_id__ty
 mf query --metrics average_purchase_price --group-by metric_time,user_id__type # In dbt Core
 ```
 
+#### SQL examples
+
+These SQL examples show how MetricFlow handles both left join and full outer join scenarios in practice:
+
+<Tabs>
+<TabItem value="SQL example for left join"> 
+
+Using the previous example for `transactions` and `user_signup` semantic models, this shows a left join between those two semantic models.
+
+```sql
+select
+  transactions.user_id,
+  transactions.purchase_price,
+  user_signup.type
+from transactions
+left outer join user_signup
+  on transactions.user_id = user_signup.user_id
+where transactions.purchase_price is not null
+group by
+  transactions.user_id,
+  user_signup.type;
+```
+</TabItem>
+
+<TabItem value="SQL example for outer joins"> 
+
+If you have multiple `fct` models, let's say `sales` and `returns`, MetricFlow uses full outer joins to ensure all data points are captured. 
+
+This example shows a full outer join between the `sales` and `returns` semantic models.
+
+```sql
+select
+  sales.user_id,
+  sales.total_sales,
+  returns.total_returns
+from sales
+full outer join returns
+  on sales.user_id = returns.user_id
+where sales.user_id is not null or returns.user_id is not null;
+```
+
+</TabItem>
+</Tabs>
+
 ## Multi-hop joins
 
 MetricFlow allows users to join measures and dimensions across a graph of entities by moving from one table to another within a graph. This is referred to as "multi-hop join".