Enhancing search language

website/docs/reference/dbt-commands.md

@@ -11,7 +11,7 @@ A key distinction with the tools mentioned, is that dbt Cloud CLI and IDE are de
 
 ## Parallel execution
 
-dbt Cloud allows for parallel execution of commands, enhancing efficiency without compromising data integrity. This enables you to run multiple commands at the same time, however it's important to understand which commands can be run in parallel and which can't.
+dbt Cloud allows for concurrent execution of commands, enhancing efficiency without compromising data integrity. This enables you to run multiple commands at the same time. However, it's important to understand which commands can be run in parallel and which can't.
 
 In contrast, [`dbt-core` _doesn't_ support](/reference/programmatic-invocations#parallel-execution-not-supported) safe parallel execution for multiple invocations in the same process, and requires users to manage concurrency manually to ensure data integrity and system stability.
 

website/docs/reference/programmatic-invocations.md

@@ -25,9 +25,9 @@ for r in res.result:
 
 ## Parallel execution not supported
 
-[`dbt-core`](https://pypi.org/project/dbt-core/) doesn't support [safe parallel execution](/reference/dbt-commands#parallel-execution) for multiple invocations in the same process. This means it's not safe to run multiple dbt commands at the same time. It's officially discouraged and requires a wrapping process to handle sub-processes. This is because:
+[`dbt-core`](https://pypi.org/project/dbt-core/) doesn't support [safe parallel execution](/reference/dbt-commands#parallel-execution) for multiple invocations in the same process. This means it's not safe to run multiple dbt commands concurrently. It's officially discouraged and requires a wrapping process to handle sub-processes. This is because:
 
-- Running simultaneous commands can unexpectedly interact with the data platform. For example, running `dbt run` and `dbt build` for the same models simultaneously could lead to unpredictable results.
+- Running concurrent commands can unexpectedly interact with the data platform. For example, running `dbt run` and `dbt build` for the same models simultaneously could lead to unpredictable results.
 - Each `dbt-core` command interacts with global Python variables. To ensure safe operation, commands need to be executed in separate processes, which can be achieved using methods like spawning processes or using tools like Celery.
 
 To run [safe parallel execution](/reference/dbt-commands#available-commands), you can use the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation) or [dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud), both of which does that additional work to manage concurrency (multiple processes) on your behalf.