Explore the future of data management with BigQuery multimodal tables. Discover how to integrate structured and unstructured data (such as text, images, and video) into a single table with full data manipulation language (DML) support. This session demonstrates how unified tables unlock the potential of unstructured data through easy extraction and merging, simplify Vertex AI integration for downstream workflows, and enable unified data discovery with search across all data.

Learn how generative AI can enhance data workflows and analysis. This session demonstrates how to access and use Gen AI models in BigQuery, including new features like open source model support and structured output from Gemini. Accelerate your data analysis with the latest AI innovations available directly in BigQuery.

BigQuery Studio and BigFrames are a powerful combination for scalable data science and analytics. Unify data management, analysis, and collaboration with BigQuery Studio’s intuitive interface. Scale data science and machine learning with BigFrames’ powerful Python API. Get deeper insights, faster.

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BigQuery allows you to generate multimodal embeddings and perform vector searches directly on your data without complex preprocessing steps. Simplify the process of finding relevant data, identifying patterns and trends, and clustering similar objects together.

Learn how to generate embeddings using familiar BigQuery SQL syntax with multimodal inputs (text, images, audio). We’ll then review how to use BigQuery’s vector search capabilities to explore data in new and innovative ways, leading to faster decision-making and improved insights.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.