Take the next step in your AI/ML journey with streaming data. Learn to deploy and manage complete ML pipelines to run inference and predictions, classify images, run remote inference calls, build a custom model handler, and much more with the latest innovations in Dataflow ML. Learn how Spotify leveraged Dataflow for large-scale generation of ML podcast previews and how they plan to keep pushing the boundaries of what’s possible with data engineering and data science to build better experiences for their customers and creators.

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Businesses everywhere have the opportunity to drive transformational impact by leveraging streaming data to make decisions and build experiences that delight users. In this session you will learn how MercadoLibre processes tens of billions of messages across thousands of applications to drive business impact. You will also learn about exciting new product announcements ranging from native ingest capabilities in Cloud Pub/Sub to new efficiency features in Dataflow to support for OSS technologies.

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Attention developers! Are you struggling with the complexities of integrating Al/ML into your apps? Join this practical session where we'll explore how MongoDB Atlas and Google Cloud's offerings like Vertex Al, Gemini, Codey, BigQuery, and Dataflow, provide a comprehensive toolkit for developers. In completing this session, you'll have the tools and confidence to embark on your own Al/ML journey! By attending this session, your contact information may be shared with the sponsor for relevant follow up for this event only.

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Natural language is an ideal interface for many real time applications such as inventory tracking, patient journey, field sales, and other on-the-go situations. However, these real time applications also require up to date and accurate information, which necessitates a real time RAG architecture. In this session, we will demonstrate how you can build an accurate and up to date real time generative AI application using a combination of Dataflow and graph databases.

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We will introduce some core Bigtable data concepts, write some data and explore it in the Cloud Console. Then we'll jump into using techniques to analyze the data in other tools, primarily BigQuery and Looker. We will set up the "Bigtable change streams to BigQuery" Dataflow pipeline, ingest data, query the change log in BigQuery and use Looker to create a visual dashboard. Throughout, we'll compare and contrast different ways to work with your big data in Bigtable to build a foundational understanding of best practices.

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U.S. floods cause ~$3B in damage annually. The National Oceanic and Atmospheric Administration predicts changing water levels, giving scientists and managers time to act. However, the massive archive of forecasts is too complex for typical users. Learn how BYU and U of Alabama, with SADA and Google, are using BigQuery, Cloud Run, DataFlow, and API Gateway to make these forecasts accessible for mobile apps, flood-warning systems, and more, addressing crucial concerns like rising river levels or the likelihood of flooding.

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Connected vehicle telemetry has data that can be used to gain insights into vehicle performance, driver behavior, and fleet operations using AI technology. We will discuss how Ford uses Bigtable to collect, store, and analyze connected vehicle telemetry data in conjunction with BigQuery, Pub/Sub and Dataflow, a recipe applicable to many time series use cases. Get some of the insights we have gained from this data, how we have used these insights to improve our fleet operations and also some new Bigtable features we‘re most excited about.

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