Data clean rooms is now in
preview. Data clean rooms provide a secure environment in which multiple parties can share, join, and analyze their data assets without moving or revealing the underlying data. To learn more, see the following topics:
Duet AI in BigQuery, an AI-powered collaborator in Google Cloud, can help you complete, generate, and explain SQL queries. This feature is in preview.
Feature
BigQuery Studio is now in
preview. BigQuery Studio offers features to make it easier for you to discover, explore, analyze, and run inference on data in BigQuery, including:
Python notebooks, powered by
Colab Enterprise.
Notebooks provide one-click Python development runtimes, and built-in
support for
BigQuery DataFrames.
Asset management and version history for notebooks and saved queries,
powered by
Dataform.
Feature
BigQuery DataFrames is now in preview. BigQuery DataFrames is a Python API that you can use to analyze data and perform machine learning tasks in BigQuery.
BigQuery DataFrames consists of the following parts:
bigframes.pandas implements a DataFrame API (with partial Pandas compatibility) on top of BigQuery.
bigframes.ml implements a Python API for BigQuery ML (with partial scikit-learn compatibility).
Feature
Data clean rooms is now in preview. Data clean rooms provide a secure environment in which multiple parties can share, join, and analyze their data assets without moving or revealing the underlying data. To learn more, see the following topics:
Feature
Duet AI in BigQuery, an AI-powered collaborator in Google Cloud, can help you complete, generate, and explain SQL queries. This feature is in preview.
Feature
BigQuery Studio is now in preview. BigQuery Studio offers features to make it easier for you to discover, explore, analyze, and run inference on data in BigQuery, including:
Feature
BigQuery DataFrames is now in preview. BigQuery DataFrames is a Python API that you can use to analyze data and perform machine learning tasks in BigQuery. BigQuery DataFrames consists of the following parts:
bigframes.pandas
implements a DataFrame API (with partial Pandas compatibility) on top of BigQuery.bigframes.ml
implements a Python API for BigQuery ML (with partial scikit-learn compatibility).Get started with BigQuery DataFrames by using the BigQuery DataFrames quickstart.
Feature
The following Generative AI features are now generally available (GA) in BigQuery ML:
ML.GENERATE_TEXT
function with an LLM-based remote model to perform generative natural language tasks on text stored in BigQuery tables.Try these features with the Generate text by using a remote model and the ML.GENERATE_TEXT function tutorial.
https://cloud.google.com/bigquery/docs/release-notes#August_29_2023