BigQuery Studio lets analytics practitioners use SQL, Python, Spark or natural language directly within BigQuery, to streamline analytics workflows.

By integrating Vertex AI foundation models in BigQuery, you can analyze unstructured data from right inside BigQuery.

BigQuery ML inference engine lets you run inference over custom models, remote models, and pretrained models within your machine learning workflow.

You can now generate text embeddings in BigQuery and apply them to downstream application tasks using familiar SQL commands.

TraceMark’s sustainable sourcing monitoring platform provides transparency into global supply chains about the sourcing of raw materials.

Carto’s conversational GIS relies on BigQuery to provide information to generative AI, while BigQueryML connects to Vertex AI and PaLM2.

Atlas AI‘s geospatial artificial intelligence platform that helps organizations anticipate changing societal conditions to help them make investment decisions.

The new BigQuery connector to Google Earth Engine improves ease-of-use and enables new analyses that combine raster and tabular data.

BigQuery, PubSub, Scheduler, Monitoring and more work together to make your DevOps processes easier with sampling data.

The new, automated open-source data migration tool moves Teradata, Hive, Redshift, and Oracle data warehouses from on-premises to BigQuery.

When it comes to geospatial data, BigQuery can help you store and analyze it, while Tableau can provide powerful visualization capabilities.

Read about how BigQuery now allows you to use manifest files for querying open table formats.

Learn how new SQL functions for BigQuery JSON give you more capabilities in dealing with JSON data.

Built on BigQuery, Weather Source makes weather analytics simple and accessible so organizations can understand how weather impacts their business.