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    Thursday, October 22 · 9:00 AM CDT · Virtual

    Understanding the Databricks Genie Landscape

    Databricks Genie is now a family of products, not a single feature. Genie One, Genie Agents, Genie Ontology, Genie Code, each solves a different problem and sits in a different part of the stack. If you are the one being asked to design, govern and build this, you need a clear map before you commit. Join Polestar Analytics and Databricks to walk the Genie landscape end to end and see how the pieces fit together on Databricks.
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    Speakers
    Meet the Minds Behind the Conversation
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    Speaker
    Vishal Vibhandik
    Vishal Vibhandik
    Partner Solutions Architect
    Databricks
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    Vishal Vibhandik
    Partner Solutions Architect
    Databricks
    Vishal is an IT professional with over 20 years architecting and delivering software and data platforms for Fortune 500 companies. A proven Solution Architect, he designs data lakes, complex pipelines and big data systems on-premise and across AWS, Azure and GCP, and is a proven leader in Hadoop and cloud migrations. AWS certified in Solution Architecture and Data Analytics, with deep expertise in Databricks, Spark, Kafka and Scala, he has managed the Databricks partner alliance and mentored 200+ engineers.
    Speaker
    Bablu Chakraborty
    Bablu Chakraborty
    Principal Solution Architect
    Polestar Analytics
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    Bablu Chakraborty
    Principal Solution Architect
    Polestar Analytics
    Bablu is a technology leader with over 20 years across cloud, Generative AI, Agentic AI, big data, data warehousing and analytics. He has guided enterprises through cloud migrations on Azure, GCP and AWS, and is an expert at unlocking data through data mesh and data products. Adept at solution and application architecture, he designs high-performance, scalable data models and champions data governance, data quality and engineering best practices, working closely with leadership to turn vision into advanced analytics solutions.
    Speaker
    Ankush Mehrotra
    Ankush Mehrotra
    Solution Architect
    Polestar Analytics
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    Ankush Mehrotra
    Solution Architect
    Polestar Analytics
    Ankush is an experienced' Solution Architect specializing in cloud, Generative AI, Agentic AI, big data, data warehousing, analytics, and modern data engineering. He has experience across Azure, AWS, and GCP, designing scalable, high-performance cloud and data solutions. He brings expertise in solution and application architecture, data platforms, integration, governance, and engineering best practices, helping organizations leverage emerging technologies to build innovative, reliable, and business-focused solutions.
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    Session Agenda
    What We'll Cover
    No marketing pitch and no slideware, just a practical, sixty-minute working session mapping the Databricks Genie landscape
    01
    How the Databricks Genie family fits together: Genie One,Genie Code, Genie Agents, Genie Ontology and where each one belongs
    02
    What Databricks Genie Ontology is, why context lives there, and how it grounds answers in governed data
    03
    How governance and Unity Catalog carry over so agents stay inside existing permissions
    04
    What it takes to prepare your data estate so Genie returns accurate, trustworthy answers
    05
    How Databricks Genie turns business questions into governed queries across your Delta tables
    06
    What solution architects and platform leads should plan for when business teams start asking for access
    Who Should Attend
    Built for Practitioners, Not Spectators
    This session is for the people who have to turn Databricks Genie from announcement into production, and anyone curious how the landscape fits together. Real architecture, real experience, and takeaways you can act on.
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    Solution architects designing data and AI platforms on Databricks
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    Data engineers building pipelines that feed Databricks Genie and its ontology
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    ML engineers working with agents, context and governed data
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    Platform leads responsible for governance, access and scale
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    Teams evaluating where the Databricks Genie products fit their architecture
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    Anyone who needs a clear map of the Databricks Genie landscape before they build
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