Simplify your AI workflow with autonomous embedding generation in BigQuery
BigQuery autonomous embedding generation treats embeddings as a managed part of your table, making it easier to get your data AI-ready.
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Modern Software Development For Today's Systems & Applications
New BigQuery global queries let you explore distributed data with a single SQL statement
The preview of global queries in BigQuery lets you query data stored in different geographic locations with a single, standard SQL query, with no ETL.
How to build a data agent with BigQuery and CloudSQL
Discover how to build a powerful data agent using ADK, BigQuery and CloudSQL. This video guides you through transforming unstructured data into structured knowledge, enabling intelligent applications. Watch along and learn how to create RAG pipelines, leverage Gemini for vector embeddings, and automate processes with Dataflow to achieve nuanced, context aware insights. Chapters: Speaker: Debi Cabrera Products Mentioned: BigQuery, CloudSQL, Agentverse, Gemini, Agent Development Kit.
Introducing Conversational Analytics in BigQuery
Conversational Analytics in BigQuery in preview brings a sophisticated AI-powered reasoning engine directly into BigQuery Studio.
BigQuery AI supports Gemini 3.0, simplified embedding generation and new similarity function
BigQuery gen AI functions AI.GENERATE and AI.GENERATE_TABLE are now GA, and can be used with the new AI.EMBED and AI.SIMILARITY.
Introducing BigQuery managed and SQL-native inference for open models
BigQuery now supports managed and SQL-native inference for Hugging Face and Vertex AI Model Garden open models.
Vibe querying: Write SQL queries faster with Comments to SQL in BigQuery
Comments to SQL in BigQuery is an AI-powered feature that bridges the gap between human language and structured data queries. Read to learn more.
BigQuery Migration Service: Validation and optimization
You’ve moved your data to Google Cloud. Now it is time to make sure it’s accurate, secure, and cost effective. This video concludes our migration series by focusing on the critical steps following data transfer from Databricks, Teradata, Snowflake, Cloudera and many other platforms. You’ve moved your data to Google Cloud. Now it is time to make sure it’s accurate, secure, and cost effective. This video concludes our migration series by focusing on the critical steps following data transfer from Databricks, Teradata, Snowflake, Cloudera and many other platforms.
Build data analytics agents faster with BigQuery's fully managed, remote MCP server
The new fully managed remote BigQuery MCP server makes it easier to build intelligent data AI agents.
BigQuery Migration Service: SQL and data transfer
Following your migration assessment, it is time to execute the transfer of your data and SQL queries into Google Cloud. This video dives into the specific tools and services that simplify migrating workloads from Snowflake, Teradata, Cloudera, and Databricks into BigQuery, Dataproc, and Google Cloud Storage.