BigQuery workflows have been renamed to BigQuery pipelines in the Google Cloud console

## Announcement BigQuery workflows have been renamed to BigQuery pipelines in the Google Cloud console. For more information, see [Introduction to BigQuery pipelines](https://cloud.google.com/bigquery/docs/workflows-introduction). ## Feature You can now use [repositories](https://cloud.google.com/bigquery/docs/repository-intro) and [workspaces](https://cloud.google.com/bigquery/docs/workspaces-intro) in BigQuery to perform version control. Repositories perform version control on files by using Git to record changes and manage file versions. You can use workspaces within repositories to edit the code stored in the repository. You can have a repository use Git directly on BigQuery, or you can [connect a repository to a third-party Git provider](https://cloud.google.com/bigquery/docs/repositories#connect-third-party). This feature is in [preview](https://cloud.google.com/products/#product-launch-stages). ## Feature You can now create [remote models](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-create-remote-model) in BigQuery ML based on the [Anthropic Claude model](https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-claude) in Vertex AI. Use the [ML.GENERATE\_TEXT function](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-generate-text) with these remote models to perform generative natural language tasks for text stored in BigQuery tables. Try this feature with the [Generate text by using the ML.GENERATE\_TEXT function](https://cloud.google.com/bigquery/docs/generate-text) tutorial. You can also evaluate Claude models by using the [ML.EVALUATE function](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate). This feature is [generally available](https://cloud.google.com/products/#product-launch-stages) (GA).