fix typo (#7007)

* Update introduction.mdx

simple typo

* Update joining-multiple-data-sources.mdx

update pre-agg index syntax

* Update using-pre-aggregations.mdx

removed warning for rollup joins between different data source types

Author: tonykau1

docs/docs-new/pages/guides/recipes/query-acceleration/joining-multiple-data-sources.mdx

@@ -71,7 +71,7 @@ cubes:
           - name
           - supplier_id
         indexes:
-          category_index:
+          - name: category_index
             columns:
               - supplier_id
 
@@ -125,7 +125,7 @@ cubes:
           - company
           - email
         indexes:
-          category_index:
+          - name: category_index
             columns:
               - id
 ```

docs/docs-new/pages/product/caching/using-pre-aggregations.mdx

@@ -587,14 +587,6 @@ pre-aggregations in Cube Store.
 
 ## Joins between pre-aggregations
 
-<WarningBox>
-
-This feature is in Preview and the API may change in a future release. Joining
-pre-aggregations **only** works with databases of the same type, support for
-joining pre-aggregations from different databases is coming soon.
-
-</WarningBox>
-
 When making a query that joins data from two different cubes, Cube can use
 pre-aggregations instead of running the base SQL queries. To get started, first
 ensure both cubes have valid pre-aggregations:

docs/docs-new/pages/product/introduction.mdx

@@ -111,7 +111,7 @@ Cube embraces and implements the three most commonly used protocols and API stan
 **SQL** is universally adopted across all the tools in the data stack. Every BI and visualization tool can query a SQL data source.
 That makes SQL an obvious choice for a communication layer to ensure interoperability. Cube implements Postgres SQL and extends
 it to support data modeling in the semantic layer. Cube adds the notion of **measure** to SQL spec, a special type that knows how to
-evaluate itself based on the definition in the data model. Every BI and visualization tool that can connect to Postgres or Refshift can connect to Cube.
+evaluate itself based on the definition in the data model. Every BI and visualization tool that can connect to Postgres or Redshift can connect to Cube.
 
 Finally, Cube exposes **robust meta API for data model introspection.** It is vital to achieve interoperability because
 it enables other tools to inspect the data model definitions and take actions, e.g. provide context to the AI agents querying the semantic