Simplify real-time data analytics and build event-driven, AI-powered applications using BigQuery and Pub/Sub. Learn to ingest and process massive streaming data from users, devices, and microservices for immediate insights and rapid action. Explore BigQuery's continuous queries for real-time analytics and ML model training. Discover how Flipkart, India’s leading e-commerce platform, leverages Google Cloud to build scalable, efficient real-time data pipelines and AI/ML solutions, and gain insights on driving business value through real–time data.

Madhive built their ad analytics and bidding infrastructure using databases and batch pipelines. When the pipeline lag got too long to bid effectively, they rebuilt from scratch with Google Cloud’s Managed Service for Apache Kafka. Join this session to learn about Madhive’s journey and dive deep into how the service works, how it can help you build streaming systems quickly and securely, and what migration looks like. This session is relevant for Kafka administrators and architects building event-sourcing platforms or event-driven systems.

Audiences around the world have almost limitless access to content that’s only a click, swipe, or voice command away. Companies are embracing cloud capabilities to evolve from traditional media companies into media-tech and media-AI companies. Join us to discover how the cloud is maximizing personalization and monetization to enable the next generation of AI-powered streaming experiences for audiences everywhere.

Overwhelmed by the complexities of building a robust and scalable data pipeline for algo trading with AlloyDB? This session provides the Google Cloud services, tools, recommendations, and best practices you need to succeed. We'll explore battle-tested strategies for implementing a low-latency, high-volume trading platform using AlloyDB and Spark Streaming on Dataproc.

Leverage Composer Orchestration to create a scalable and efficient data pipeline that meets the demands of algo trading and can handle increasing data volumes and trading activity by utilizing the scalability of Google Cloud services.

The telecom industry has always been critical to advancing how we communicate, work, and play, whether through creation of our mobile world or streaming through high bandwidth connectivity. In this session we will explore how communication service providers from around the globe are leveraging AI agents across their workforce, customer experience, field operations, network operations, and more.

Enhance your data ingestion architecture's resilience with Google Cloud's serverless solutions. Gain end-to-end visibility into your data's lineage—track each data point's transformation journey, including timestamps, user actions, and process outcomes. Implement real-time streaming and daily batch processes for Vertex AI Retail Search to deliver near real-time search capabilities while maintaining a daily backup for contingencies. Adopt best practices for data management, lineage tracking, and forensic capabilities to streamline issue diagnosis. This talk presents a scalable and fault-tolerant design that optimizes data quality and search performance while ensuring forensic-level traceability for every data movement.

Join this Cloud Talk to explore how Large Language Models (LLMs) can revolutionize your data workflows. Learn to automate SQL query generation and stream results into Confluent using Vertex AI for real-time analytics and decision-making. Dive into integrating advanced AI into data pipelines, simplifying SQL creation, enhancing workflows, and leveraging Vertex AI for scalable machine learning. Discover how to optimize your data infrastructure and drive insights with Confluent’s Data Streaming Platform and cutting-edge AI technology.

This Session is hosted by a Google Cloud Next Sponsor.
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Google's Data Cloud is a unified platform for the entire data lifecycle, from streaming with Managed Kafka, to ML feature creation in BigQuery, to global deployment via Bigtable. In this talk, we’ll give you a behind the scenes look at how Spotify's recommendation engine team uses Google's Data Cloud for their feature pipelines. Plus, we will demonstrate BigQuery AI Query Engine and how it streamlines feature development and testing. Finally, we'll explore new Bigtable capabilities that simplify application deployment and monitoring.

Unlock the potential of AI with high-performance, scalable lakehouses using BigQuery and Apache Iceberg. This session details how BigQuery leverages Google's infrastructure to supercharge Iceberg, delivering peak performance and resilience. Discover BigQuery's unified read/write path for rapid queries, superior storage management beyond simple compaction, and robust, high-throughput streaming pipelines. Learn how Spotify utilizes BigQuery's lakehouse architecture for a unified data source, driving analytics and AI innovation.

Redpanda, a leading Kafka API-compatible streaming platform, now supports storing topics in Apache Iceberg, seamlessly fusing low-latency streaming with data lakehouses using BigQuery and BigLake in GCP. Iceberg Topics eliminate complex & inefficient ETL between streams and tables, making real-time data instantly accessible for analysis in BigQuery This push-button integration eliminates the need for costly connectors or custom pipelines, enabling both simple and sophisticated SQL queries across streams and other datasets. By combining Redpanda and Iceberg, GCP customers gain a secure, scalable, and cost-effective solution that transforms their agility while reducing infrastructure and human capital costs.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

Build fully integrated streaming pipelines on Google Cloud and learn how to leverage AlloyDB, Datastream, BigQuery, Looker, and Vertex AI for real-time data analysis.

Kayak through Seattle’s lakes with AI! Discover how Gemini can take you where you want to go, through rapid prototyping with its function calling, streaming, and multimodal APIs. Learn how you can build your own immersive AI experiences faster than ever.