Ralf Götz

The TMDL view makes it easy to reuse and share semantic model objects across different semantic models. We've just launched an official TMDL Gallery in the Fabric Community - a place where you can discover and share your favorite semantic model objects as TMDL scripts, making it simple for others to reuse them. 👉 https://lnkd.in/dnzTn4gQ cc 🎯Alexander Korn, Zoe Douglas, John Kerski, Christine Payton to move your scripts from https://lnkd.in/duZ57B7M #tmdl #powerbi

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🚀 New Launch: Amazon QuickSight dashboards now in SageMaker Unified Studio With this release, SageMaker Catalog is more diverse than ever. In addition to cataloging Glue tables, Redshift tables, S3 objects, and ML models, you can now catalog Amazon QuickSight dashboards. This makes enterprise data catalogs more complete and valuable than ever. Why this matters for enterprise metadata management and data governance: ✅ One unified catalog where all your key analytics and AI assets live in a single governed inventory ✅ Governed visual insights where dashboards become governed, discoverable, and reusable assets just like datasets and models ✅ Cross team collaboration where BI engineers and decision makers can work from the same trusted dashboards used by data scientists ✅ Improved compliance by applying consistent governance policies to dashboards alongside other data assets This launch strengthens your ability to discover, govern, and trace every asset in your organization from raw data to business ready insights within the same platform. If you want to see how it works, I co-authored this blog with Ramon Jose Lopez that walks you through configuration and usage: 👉 https://lnkd.in/equ6nZZm This is a huge step toward a truly unified enterprise data catalog that connects analytics, AI, and governance in one place. Shikha Verma William Vambenepe Utkarsh Mittal Jorge A. Lopez Stephanie Shyu Camille Taylor Rick Sears Ramesh Harisaran Singh Abbas Makhdum Luis Campos Larry Weber Linda Xu #aws #datagovernance #SMUS #amazonsagemaker #metadata #bi

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Databricks meets Fabric — for real this time. Unity Catalog mirroring is now GA, and it changes the game for multi-cloud data teams. 🧵 Data engineers have long been juggling two worlds: ☁️ One in Databricks, built on open lakehouse principles 🧱 Another in Fabric, optimized for Microsoft-native analytics But getting governed, trusted data to flow between them? That’s been messy… until now. The new Unity Catalog Mirroring (GA) lets you: 🔹 Mirror tables from Azure Databricks directly into Microsoft Fabric 🔹 Maintain governance — same permissions, same lineage 🔹 Query Databricks tables in Fabric with no duplication or syncing 🔹 Use mirrored data in Power BI, Notebooks, Pipelines, Lakehouses 🔹 Build true cross-platform lakehouse architectures without data silos Say your data scientists are building features in Databricks, and your business teams want to analyze that data in Power BI — now they can, securely, without lifting or copying anything. The wall between Microsoft Fabric and Databricks just got a doorway. And it’s governed, tracked, and real-time. Get the full information in fabric blog post - link in comments Are you planning to integrate Fabric + Databricks in your architecture? Or already doing it? I’d love to hear how you're approaching it👇 #MicrosoftFabric #Databricks #UnityCatalog #DataGovernance #DataStormDetectives #DataEngineering #DataArchitecture #PowerBI #CloudAnalytics #Lakehouse #GenAI

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This is a big win for Spark developers! Snowpark Connect for Apache Spark™ is now in Public Preview. You can now run Spark code directly on Snowflake’s engine—unlocking faster performance and cost efficiency. Say goodbye to complex tuning and infrastructure management, and enjoy the best of both worlds for your data pipelines and Iceberg projects. #Snowflake #ApacheSpark #Snowpark #DataEngineering #Iceberg #SparkOnSnowflake https://lnkd.in/gp6ySYfb

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Snowflake just announced that Cortex AI SQL Functions are now supported in Dynamic Tables with incremental refresh ❄️ This should help lower the AI (and transformation) cost for anyone who is using Cortex in DTs.

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New in Databricks (Beta): Data Classification in Unity Catalog 🚀 We’ve introduced automated data classification in Unity Catalog—helping you quickly identify and tag sensitive data like PII or confidential information. Why it matters: 👉 Automated & incremental scanning – saves time and cost 👉 Better governance – pair with ABAC and tag policies to protect sensitive data automatically 👉 Less manual work – focus on action, not tagging Availability and prerequisites: 🔹 Available now (in Beta) on AWS, Azure, and GCP 🔹 Requires serverless compute As always, we’re very open to feedback! 👂 Feedback/questions: [email protected] 📄 Learn more: https://lnkd.in/d-PdfQDx PS. What is this "new" Beta release thing at Databricks?? 🤨 📄 Learn more: https://lnkd.in/dt9pj42d

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GPT‑5 Is Now Live in Azure AI Foundry — Here’s What It Means for You.. Let's Discuss!   Microsoft has officially launched GPT‑5 across Azure AI Foundry, offering businesses the most advanced reasoning-powered AI yet, now tailored for real-world scale and reliability (Microsoft Azure).   ** Key Benefits for Azure & AI Users:**   Adaptive AI Flexibility: From deep reasoning to ultra-low latency responses, the GPT‑5 family (including mini, nano, and chat variants) is orchestrated via Azure’s model router, which optimizes model selection for performance and cost — customers can cut inferencing costs by up to 60% with no quality trade-offs (Microsoft Azure). Sharper Enterprise Reasoning: Whether you're automating multi-step workflows, generating complex code, or managing large-context Q&A, GPT‑5 does it with clarity and auditability, making it mission-ready for analytics, developer productivity, and customer service scenarios (Microsoft Azure). Secure and Governed by Design: The Azure AI Foundry ecosystem ensures enterprise-grade security, with built-in safety layers, content filtering, and continuous monitoring through Azure Monitor, Defender for Cloud, and Purview — giving customers both innovation and trust (Microsoft Azure). Faster, Smarter Development: GPT-5 is now powering GitHub Copilot, VS Code, and Microsoft 365 Copilot — enabling developers and enterprise users to automate faster, code smarter, and engage in longer, more coherent multi-turn conversations with trust and context awareness (Source).   For organizations ready to move beyond pilot projects, GPT-5 in Azure AI Foundry delivers a powerful, scalable pathway — blending intelligent AI with operational excellence and governance. Curious how this could transform your AI journey? https://lnkd.in/g7GCn2dE #AzureAI #AITransformation #GPT5 #EnterpriseAI #CloudInnovation #SaxonAI  

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This is one of the most principled and well thought out approaches I've seen thus far on the business impact of AI. Recommended reading for any leader who is driving change in their organization via technology. https://lnkd.in/d5FnaDbv

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