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    From Dashboards to Autonomous Action: Why You Need to Attend Google Cloud Labs
    googlecloud

    From Dashboards to Autonomous Action: Why You Need to Attend Google Cloud Labs

    Joey Lynne Hernandez June 8, 2026
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    The era of passive data analytics is over. Today, the most forward-thinking data teams aren't just...

    The era of passive data analytics is over. Today, the most forward-thinking data teams aren't just building dashboards to show what happened yesterday—they are building the foundational platforms that power applied, Agentic AI.

    But bridging the gap between traditional data engineering and the new frontier of agentic workflows isn't something you can learn just by reading whitepapers. You need to get your hands on the tools.

    That’s exactly why we’re hitting the road with the Google Cloud Labs: Data Cloud series, coming to Toronto and Chicago this month.

    ##Not Your Average Lecture Series

    This isn't a day of sitting back and watching slides. It’s an immersive, hands-on workshop where you’ll spend the day alongside Google engineers building real solutions.

    Whether you’re a Data Engineer, Data Scientist, or Data Analyst, this lab is designed to give you the practical skills and architectural patterns needed to make your enterprise data AI-ready. We’ll be diving deep into the actual implementation of Google Cloud’s latest data and AI services.

    ##What You Will Build

    Bring your laptop, because throughout the day, you will be working through a series of live labs to build out a complete, agentic workflow powered by your data. Here is a sneak peek at what’s on the agenda:

    • Mastering Governed Data Ingestion: You'll build unified, governed data pipelines across multi-cloud sources using Spark and Knowledge Catalog.
    • Unlocking Multimodal Analytics: We’ll move beyond text and numbers, using Gemini in BigQuery to extract insights from unstructured and multimodal data.
    • Scaling Vector Search: You’ll get hands-on with AlloyDB, learning how to scale vectorized search for high-performance, context-aware AI applications.
    • Engineering Agentic Workflows: Finally, we’ll bring all these pieces together. Using BigQuery Graph and the Agent Development Kit (ADK), you will build autonomous, agentic workflows that can actually take action based on your data.

    ##Secure Your Spot

    Space for these in-person labs is strictly limited to ensure everyone gets dedicated time with our engineers and hands-on support during the exercises.

    If you have a strong data foundation and are ready to dive deeper into applied AI, register today:

    • Toronto: Register for the Toronto Lab (June 25th at the Delta Hotels Toronto)
    • Chicago: Register for the Chicago Lab (June 30th at the Google Chicago Office)

    Tags

    googlecloudagentsdataengineering

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