Update release-notes.md

website/docs/docs/dbt-versions/release-notes.md

@@ -19,19 +19,25 @@ Release notes are grouped by month for both multi-tenant and virtual private clo
 [^*] The official release date for this new format of release notes is May 15th, 2024. Historical release notes for prior dates may not reflect all available features released earlier this year or their tenancy availability.
 
 ## July 2024
-- **New:** [Merge jobs](/docs/deploy/merge-jobs) for implementing [continuous deployment (CD)](/docs/deploy/continuous-deployment) workflows are now GA in dbt Cloud. Previously, you had to either set up a custom GitHub action or manually build the changes every time a pull request is merged.  
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+- **New:** [Merge jobs](/docs/deploy/merge-jobs) for implementing [continuous deployment (CD)](/docs/deploy/continuous-deployment) workflows are now GA in dbt Cloud. Previously, you had to either set up a custom GitHub action or manually build the changes every time a pull request is merged.
+- **New**: The ability to lint your SQL files from the dbt Cloud CLI is now available. To learn more, refer to [Lint SQL files](/docs/cloud/configure-cloud-cli#lint-sql-files).
 - **Behavior change:** dbt Cloud IDE automatically adds a `--limit 100` to preview queries to avoid slow and expensive queries during development. Recently, dbt Core changed how the `limit` is applied to ensure that `order by` clauses are consistently respected. Because of this, queries that already contain a limit clause might now cause errors in the IDE previews. To address this, dbt Labs plans to provide an option soon to disable the limit from being applied. Until then, dbt Labs recommends removing the (duplicate) limit clause from your queries during previews to avoid these IDE errors.
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 - **Enhancement:** Custom configurations are now supported by generic data tests. Use this to configure how dbt should run the data test (for example, specifying a Snowflake virtual warehouse different from the one in your connection). To learn more, refer to [Specify custom configurations for generic data tests](/reference/data-test-configs#specify-custom-configurations-for-generic-data-tests).
 
   Support for this configuration is available in dbt Cloud when selecting "Keep on latest version." Specifying custom configurations for data tests will become available in dbt Core later this year.
 
 - **Enhancement**: Introducing a revamped overview page for dbt Explorer, available in beta. It includes a new design and layout for the Explorer homepage. The new layout provides a more intuitive experience for users to navigate their dbt projects, as well as a new **Latest updates** section to view the latest changes or issues related to project resources. To learn more, refer to [Overview page](/docs/collaborate/explore-projects#overview-page).
-- **Enhancement**: The dbt Semantic Layer now offers more granular control by supporting multiple data platform credentials, which can represent different roles or service accounts. Available for dbt Cloud Enterprise plans, you can map credentials to service tokens for secure authentication. Refer to [Set up dbt Semantic Layer](/docs/use-dbt-semantic-layer/setup-sl#set-up-dbt-semantic-layer) for more details.
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+#### dbt Semantic Layer
 - **New**: Introduced the [`dbt-sl-sdk` Python software development kit (SDK)](https://github.com/dbt-labs/semantic-layer-sdk-python) Python library, which provides you with easy access to the dbt Semantic Layer with Python. It allows developers to interact with the dbt Semantic Layer APIs and query metrics and dimensions in downstream tools. Refer to the [dbt Semantic Layer Python SDK](/docs/dbt-cloud-apis/sl-python) for more information.
-- **New**: The ability to lint your SQL files from the dbt Cloud CLI is now available. To learn more, refer to [Lint SQL files](/docs/cloud/configure-cloud-cli#lint-sql-files).
 - **New**: Introduced Semantic validations in CI pipelines. Automatically test your semantic nodes (metrics, semantic models, and saved queries) during code reviews by adding warehouse validation checks in your CI job using the `dbt sl validate` command. You can also validate modified semantic nodes to guarantee code changes made to dbt models don't break these metrics. Refer to [Semantic validations in CI](/docs/deploy/ci-jobs#semantic-validations-in-ci) to learn about the additional commands and use cases.
+- **New**: We now expose the `meta` field within the [config property](/reference/resource-configs/meta) for dbt Semantic Layer metrics in the [JDBC and GraphQL APIs](/docs/dbt-cloud-apis/sl-api-overview) under the `meta` field.
+- **New**: Added a new command in the dbt Cloud CLI called `export-all`, which allows you to export multiple or all of your saved queries. Previously, you had to explicitly specify the [list of saved queries](/docs/build/metricflow-commands#list-saved-queries).
+- **Enhancement**: The dbt Semantic Layer now offers more granular control by supporting multiple data platform credentials, which can represent different roles or service accounts. Available for dbt Cloud Enterprise plans, you can map credentials to service tokens for secure authentication. Refer to [Set up dbt Semantic Layer](/docs/use-dbt-semantic-layer/setup-sl#set-up-dbt-semantic-layer) for more details.
+- **Fix**: Addressed a bug where unicode query filters (such as Chinese characters) were not working correctly in the dbt Semantic Layer Tableau integration.
+- **Fix**: Resolved a bug with parsing certain private keys for BigQuery when running an export.
+- **Fix**: Addressed a bug that caused a "closed connection" error to be returned when querying or running an Export.
+- **Fix**: Resolved an issue in dbt Core where, during partial parsing, all generated metrics in a file were incorrectly deleted instead of just those related to the changed semantic model. Now, only the metrics associated with the modified model are affected.
 
 ## June 2024
 - **New:** Introduced new granularity support for cumulative metrics in MetricFlow. Granularity options for cumulative metrics are slightly different than granularity for other metric types. For other metrics, we use the `date_trunc` function to implement granularity. However, because cumulative metrics are non-additive (values can't be added up), we can't use the `date_trunc` function to change their time grain granularity.