Dataform now lets you automate the creation of BigLake tables for Apache Iceberg in BigQuery

## Feature Feature Dataform now lets you automate the creation of[BigLake tables for Apache Iceberg in BigQuery](https://cloud.google.com/dataform/docs/create-tables#create-iceberg-table). This feature is[generally available](https://cloud.google.com/products#product-launch-stages)(GA). ## Feature Feature You can now use [Gemini 3.0](https://cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro)when you call generative AI functions in BigQuery, such as [AI.GENERATE](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate). You must use the full global endpoint argument: `https://aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/global/publishers/google/models/gemini-3-pro-preview`. ## Feature Feature BigQuery ML now supports the following[generative AI functions](https://cloud.google.com/bigquery/docs/generative-ai-overview): * [AI.GENERATE](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate): generate free text to accomplish a wide range of tasks, such as translation, summarization, and classification, on any unstructured data, including images, audio, video, and documents. It can also perform entity extraction and generate structured output. This function is[generally available](https://cloud.google.com/products/#product-launch-stages)(GA). * [AI.EMBED](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-embed): turn text, image, audio, video, or documents into embeddings. This function is in [Preview](https://cloud.google.com/products/#product-launch-stages). * [AI.SIMILARITY](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-similarity): compute the semantic similarity between pairs of text, pairs of images, or across text and images. This function is in[Preview](https://cloud.google.com/products/#product-launch-stages). * You can use the[AI.GENERATE\_BOOL](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate-bool),[AI.GENERATE\_DOUBLE](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate-double), and[AI.GENERATE\_INT](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate-int)functions to generate scalar values, which are convenient for filtering, scoring, and counting purposes. * Each of these functions supports[authentication with end-user credentials (EUC)](https://cloud.google.com/bigquery/docs/permissions-for-ai-functions#run%5Fgenerative%5Fai%5Fqueries%5Fwith%5Fend-user%5Fcredentials)to set up the necessary Vertex AI permissions. BigQuery ML now supports the following table-valued generative AI functions: * [AI.GENERATE\_TABLE](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-generate-table): generate a table of structured output from unstructured data including text, images, audio, and video. * [AI.GENERATE\_TEXT](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate-text)is the new, preferred version of `ML.GENERATE_TEXT`, which has the same functionality but with simplified column output names. * [AI.GENERATE\_EMBEDDING](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate-embedding)is the new, preferred version of `ML.GENERATE_EMBEDDING`, which has the same functionality but with simplified column output names. * These functions are all[generally available](https://cloud.google.com/products/#product-launch-stages)(GA). ## Feature Feature You can now [publish data insights](https://cloud.google.com/bigquery/docs/data-insights#modes), including query recommendations and auto-generated table and column descriptions, to the Dataplex Universal Catalog. This feature is in[Preview](https://cloud.google.com/products/#product-launch-stages).