# Deutsche Börse uses GenAI for data migration _Deutsche Börse uses a custom Databricks App and generative AI to automate the migration of thousands of analytics notebooks, cutting redevelopment time by over 90%._ **Updated:** 2026-08-22 **Published:** 2026-05-19 **Source:** https://www.startuphub.ai/ai-news/technology/2026/deutsche-b-rse-uses-genai-for-data-migration --- Deutsche Börse Group is leveraging generative AI to tackle the monumental task of migrating thousands of analytics notebooks. Facing a 2027 deadline to move from Cloudera's soon-to-be-decommissioned Zeppelin notebooks to Databricks, the financial services giant developed a custom Databricks App to automate the process. Cloudera DeadlineDriverFrom the articleFacing a 2027 deadline to move from Cloudera's soon-to-be-decommissioned Zeppelin notebooks to Databricks, the financial services giant developed a custom Databricks App to automate the process.Thousands of NotebooksDriverover 2,000 users and a vast number of notebooks with complex logicFrom the article 6 mentionsDeutsche Börse Group is leveraging generative AI to tackle the monumental task of migrating thousands of analytics notebooks.Custom Databricks AppCoreFrom the article 3 mentionsFacing a 2027 deadline to move from Cloudera's soon-to-be-decommissioned Zeppelin notebooks to Databricks, the financial services giant developed a custom Databricks App to automate the process.GenAI for LogicCoregenerative AI reconstructs complex notebook logic, not just structureFrom the article 4 mentionsThe challenge involved over 2,000 users and a vast number of notebooks, many containing complex logic and institutional knowledge.Automate StructureContextapp handles deterministic aspects: paragraph to cell, syntax translationFrom the articleFacing a 2027 deadline to move from Cloudera's soon-to-be-decommissioned Zeppelin notebooks to Databricks, the financial services giant developed a custom Databricks App to automate the process.90% Time CutOutcomecutting redevelopment time by over 90% from manual rewriteFrom the articleThe result is a dramatic reduction in migration time.Faster MigrationEffectenables migration from hours to minutes for thousands of notebooksFrom the article 5 mentionsThis hybrid approach, automating the predictable and delegating the complex to AI, is key to the success of this Databricks generative AI migration. The challenge involved over 2,000 users and a vast number of notebooks, many containing complex logic and institutional knowledge. A manual rewrite would have taken years, prompting the development of an AI-assisted solution. The core innovation, as detailed on the [Databricks](https://www.databricks.com/blog/how-deutsche-borse-built-generative-ai-tool-tackle-large-scale-migration-zeppelin-notebooks) blog, lies in separating structural conversion from logic reconstruction. ## Automating the Structure, AI for Logic The Databricks App handles the deterministic aspects: transforming Zeppelin's paragraph format into Databricks cells, translating interpreter syntax, and reformatting metadata. This structural conversion preserves the original content precisely. The true power comes in the next step: logic reconstruction. For each converted notebook, the app generates a context-aware prompt tailored to Deutsche Börse's specific Zeppelin environment, including custom interpreters and data source references. This prompt is fed into Databricks Genie, an AI assistant that asks clarifying questions and rebuilds the notebook's logic. This hybrid approach, automating the predictable and delegating the complex to AI, is key to the success of this Databricks generative AI migration. ## From Hours to Minutes The result is a dramatic reduction in migration time. Notebook redevelopment that once took hours now takes a mere 15-20 minutes per notebook. This significantly accelerates a critical cloud transformation initiative. Crucially, the tool democratizes the migration process, requiring less deep technical expertise from business users. The [Databricks Streamlines Lakehouse Migrations](/ai-news/technology/2026/databricks-streamlines-lakehouse-migrations) initiative is exemplified by this project, showcasing how platform capabilities can be combined with AI for efficiency. ## Lessons Learned Deutsche Börse highlighted several key takeaways: avoiding over-engineering, recognizing the limitations of rule-based systems for heterogeneous content, and the critical importance of context in AI prompts. Early collaboration with the platform team was also vital. This project demonstrates that AI-assisted migration is not a future concept but a present reality, transforming daunting cloud migration challenges into manageable, scalable workflows. --- Original analysis from [startuphub.ai](https://www.startuphub.ai), the #1 AI startup directory. © StartupHub.ai. All rights reserved. You may not republish this article in full without a license. Search engines and AI research tools may crawl and summarize for reference. 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