How Microsoft Fabric and Azure AI create self-healing analytics pipelines

The future of AI will be built on the data that powers our world today. That’s why 𝐎𝐫𝐚𝐜𝐥𝐞 𝐝𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐦𝐢𝐫𝐫𝐨𝐫𝐢𝐧𝐠 𝐢𝐧 𝐎𝐧𝐞𝐋𝐚𝐤𝐞, now in public preview, is a breakthrough. With Microsoft Fabric, organizations can: ▪️Integrate Oracle data natively into an AI-ready foundation without replication or ETL overhead. ▪️Accelerate AI adoption by making mission-critical Oracle workloads instantly available for analytics, modeling, and intelligent agent workflows. ▪️Enrich Oracle data with contextual insights across the business, thanks to Microsoft’s unified data platform. 𝐓𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐝𝐚𝐭𝐚 𝐢𝐬 𝐨𝐩𝐞𝐧, 𝐮𝐧𝐢𝐟𝐢𝐞𝐝, 𝐚𝐧𝐝 𝐀𝐈-𝐫𝐞𝐚𝐝𝐲. https://msft.it/6045sqDzX

Today marks a crucial juncture in the AI + Data Intelligence realm. Recent advancements are not solely transforming infrastructure but also reshaping how businesses approach growth, scalability, and competitive edges. In the realm of AI infrastructure, Nebius has clinched a monumental $17–19B AI cloud computing deal with Microsoft, bolstered by Nvidia-backed data centers in New Jersey. This underscores the increasing significance of data-centric operations in enterprise AI. On the frontlines, data and AI enterprises are forging ahead. Databricks now anticipates an annualized revenue run rate of $4B, with a substantial $1B stemming from AI offerings alone. This underscores the pivot towards unified data and AI platforms as pivotal to business strategies. In a nuanced landscape, the momentum in AI encounters a twist. A U.S. Census Bureau survey reveals a slight decline in AI adoption among major corporations, from 13.5% to approximately 12%, prompting reflections on sustainability and return on investment. Google Cloud's CEO disclosed a robust 32% year-over-year revenue surge ($13.6B in Q2), propelled by tailored AI chips and Gemini models. This accentuates the significance of vertical integration and specialized tools in a competitive cloud market. These dynamics paint a multifaceted narrative: while capital influx and innovation elevate the data-AI fusion, corporate tech integration faces heightened scrutiny and adjustments. The implications for you are clear: whether constructing data pipelines, crafting AI workflows, or designing BI dashboards, the path ahead is evident: - Ensure Scalability by preparing your data architecture (e.g., lakehouse models) for AI-driven workloads. - Emphasize Strategic ROI by prioritizing initiatives that yield tangible results, not just buzz. - Harness Toolchain unity by leveraging integrated platforms (cloud + AI + custom silicon) for distinctiveness. - Serve as an Adoption navigator by guiding enterprises through adoption challenges with practical, measurable use cases. In today's business analysis domain, AI devoid of intelligent data fusion amounts. #AI #DataIntelligence #BusinessAnalysis #DataPipelines #AIWorkflows #CloudAI #BI #TechLeadership

𝐒𝐜𝐡𝐞𝐦𝐚 𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐲: 𝐂𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐭𝐲𝐩𝐞-𝐬𝐚𝐟𝐞 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐮𝐬𝐢𝐧𝐠 𝐒𝐜𝐡𝐞𝐦𝐚𝐬 𝐚𝐧𝐝 𝐄𝐯𝐞𝐧𝐭𝐬𝐭𝐫𝐞𝐚𝐦𝐬 (𝐏𝐫𝐞𝐯𝐢𝐞𝐰) Real-Time Intelligence is an end-to-end solution in Microsoft Fabric that powers event-driven and streaming applications. It enables the extraction of insights, visualization, and action on data in motion by handling data ingestion, transformation, storage, analytics, visualization, tracking, AI, and real-time actions. 📌 𝑹𝒆𝒂𝒅 𝒃𝒍𝒐𝒈 𝒇𝒐𝒓 𝒎𝒐𝒓𝒆 𝒅𝒆𝒕𝒂𝒊𝒍𝒔: https://lnkd.in/g9FVmyKE #NextGenDataAspirants #Metadata #DataIntegration #RESTAPI #PowerBICommunity #BusinessIntelligence #SQLanalyticsendpoint Magudeswaran | Kaviya | Manikanta Reddy | Srinivasareddy | Sreethar M B | Suresh | Maureen Direro | Krishnakanth | Gopi Krishna | Satya Sekhar | Subhasis Das | RAMA | Santosh J. | Mahesh

🚀 80% of Fortune 500 companies now use Microsoft Fabric — and it’s not just about managing data anymore. It’s about unlocking knowledge. 🔍 The latest evolution? Microsoft is integrating LinkedIn’s graph database technology into Fabric to solve a key challenge in enterprise AI: understanding relationships between data entities. 🧠 While vector databases are great for semantic search, they lack context. Graph databases fill that gap by modeling connections — between customers, suppliers, systems — creating knowledge graphs that bring memory and relevance to AI. 🔄 Microsoft’s two-stage approach: Graph narrowing: Identify relevant entities through relationships. Vector zoom: Perform semantic search within that refined set. 💡 This dramatically improves AI accuracy and performance — reducing noise, speeding up responses, and enabling agentic systems with persistent memory. 📊 With native support for GraphQL, open formats, and real-time mirroring (Oracle, BigQuery), Fabric is becoming the unified data intelligence platform for enterprises. We see how this shift from data lakes to context-rich knowledge platforms can transform fraud detection, customer intelligence, and operational efficiency. https://lnkd.in/evUGSU5C 🔗 Curious how this could reshape your AI strategy? Let’s connect. #MicrosoftFabric #LinkedInGraph #EnterpriseAI #KnowledgeGraph #DataPlatform #AzureData #FinancialServices #AIInfrastructure #TechLeadership

We’re standing at a turning point for AI-powered data workflows.   Microsoft’s latest post, “Microsoft leads shift beyond data unification to organization, delivering next-gen AI readiness with new Microsoft Fabric capabilities”, lays out how “AI readiness” is evolving. Data centralization was just the start, what matters now is contextual data grounded in your operations.    Here’s what caught my attention as key wins for teams and leaders:   🔹When your data is well organized and governed, agents, analytics, and Copilot-style assistants can deliver truly useful insights, not just output. 🔹Fabric’s approach shows that AI reliability scales when backed by solid architecture, not just models. 🔹This update puts pressure on governance, ownership, and security over your data, how you collect it, store it, shape it.   If you’re building solutions, migrating platforms, or putting AI into daily workflows, this is where to focus: making data not just unified, but organized, tied to business context, and trusted.   Read the full Microsoft announcement: Fabric+ AI readiness shift https://lnkd.in/grZt6jXj   What’s your view? what’s more important?: Having all the data in one place, or having the right data surfaced at the right time?   #MicrosoftFabric #AIReadiness #DataOrganization #Analytics Microsoft Fabric #ModernWork #AVASOFT Microsoft 365 Partner

🚀 Transforming Data Analytics with Snowflake Cortex Game-changing AI is no longer a luxury—it's a necessity for competitive businesses. Snowflake Cortex is revolutionizing how we approach machine learning and artificial intelligence in the cloud. What makes Cortex exceptional? ✅ Native ML Functions: Build sophisticated models without leaving your SQL environment ✅ LLM Integration: Access industry-leading models like Mistral, Llama, and Arctic directly in Snowflake ✅ Zero Infrastructure Management: Focus on insights, not infrastructure complexity ✅ Enterprise-Grade Security: Your data never leaves Snowflake's secure perimeter The result? Data teams can now deploy AI solutions in hours, not months. From sentiment analysis to predictive forecasting, Cortex empowers organizations to unlock actionable insights from their data warehouse. Ready to accelerate your AI journey? The future of intelligent data analytics is here. 🔗 Follow me for more insights on AI, Data Analytics, and Cloud Technologies! What's your biggest challenge in implementing AI for data analytics? Share your thoughts below! 👇 Connect with me: https://lnkd.in/gbVVTEcM Snowflake Accenture #Innovation #Technology #ArtificialIntelligence #DataScience #CloudComputing #DigitalTransformation #MachineLearning #BigData #DataAnalytics #AI #Future #Business #SnowflakeData #MLOps #Analytics

Microsoft posted something that really caught my attention, new Microsoft Fabric capabilities focused on AI readiness. 👉 https://lnkd.in/gPGY3RrY   What I like about this update is the shift in mindset. 𝘍𝘰𝘳 𝘺𝘦𝘢𝘳𝘴, 𝘵𝘩𝘦 𝘤𝘰𝘯𝘷𝘦𝘳𝘴𝘢𝘵𝘪𝘰𝘯 𝘸𝘢𝘴 𝘢𝘭𝘭 𝘢𝘣𝘰𝘶𝘵 𝘶𝘯𝘪𝘧𝘺𝘪𝘯𝘨 𝘥𝘢𝘵𝘢. 𝘕𝘰𝘸, 𝘔𝘪𝘤𝘳𝘰𝘴𝘰𝘧𝘵 𝘪𝘴 𝘴𝘢𝘺𝘪𝘯𝘨: 𝘪𝘵’𝘴 𝘯𝘰𝘵 𝘫𝘶𝘴𝘵 𝘢𝘣𝘰𝘶𝘵 𝘶𝘯𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯, 𝘪𝘵’𝘴 𝘢𝘣𝘰𝘶𝘵 𝘰𝘳𝘨𝘢𝘯𝘪𝘻𝘪𝘯𝘨 𝘥𝘢𝘵𝘢 𝘴𝘰 𝘪𝘵’𝘴 𝘤𝘰𝘯𝘵𝘦𝘹𝘵𝘶𝘢𝘭, 𝘨𝘰𝘷𝘦𝘳𝘯𝘦𝘥, 𝘢𝘯𝘥 𝘳𝘦𝘢𝘥𝘺 𝘧𝘰𝘳 𝘈𝘐 𝘵𝘰 𝘢𝘤𝘵 𝘰𝘯.   Some highlights worth noting:   🔹Fabric isn’t only collecting data, it’s making sure it’s usable, secure, and trusted. 🔹Copilot and AI assistants can now work off organized, business-ready data, not just raw lakes. 🔹This makes the jump from strategy to execution a lot smoother for IT and business leaders alike.   It feels like a big step toward making AI more practical in day-to-day enterprise scenarios, not just a promise, but something you can actually operationalize. Organizing data isn’t just a tech step - it’s a business strategy. #MicrosoftFabric #AIReadiness #DataOrganization #Analytics #ModernWork #DataStrategy #DataGovernance #DataDriven #BusinessIntelligence #DataManagement #msftadvocate

At FabCon Vienna, Microsoft made it clear that just having all your data in one place isn’t enough. The real challenge is figuring out how to organize that data in a way that makes sense to both AI systems and the people who use them. Why does this matter? Well, because “AI readiness” isn’t determined by the size of a data lake, but rather by whether the data is structured, contextualized and governed to support real decisions. Fabric’s new features reflect this direction. OneLake now supports mirroring for Oracle and Google BigQuery, allows shortcuts to Microsoft Azure Blob Storage and integrates with Azure AI Search. The new Graph and Maps capabilities bring relationship modeling and geospatial context, which applies directly to supply chains, customer journeys and operational monitoring. The platform also introduces tools such as the Extensibility Toolkit and Model Context Protocol (MCP) for deeper integration into development environments. Security, performance and simplified migration from Synapse are also improved. These updates are important, but the real test is adoption. Organizations are already juggling hundreds of fragmented applications and platforms, each requiring its own management tools. Fabric's focus on estate unification and simplification could be key to reducing this complexity, but time will tell whether this holds as adoption accelerates. Integration with Azure AI Foundry also raises vendor competition; differentiation could require more than incremental features. The primary focus for customers is that these new features can provide data clarity and trust, rather than adding to the complexity of data management. The broader takeaway is that AI readiness is rapidly changing. Centralization is just the baseline. The differentiator is how data is organized so agents and people can understand it. Microsoft is pushing the conversation in that direction, but the outcome will depend on how well these capabilities scale in the complicated reality of enterprise environments. And this shift isn’t limited to data platforms—it’s the same pressure facing ERP, SCM, and other enterprise systems that are moving from static processes to agent-driven, context-rich operations. Moor Insights & Strategy Microsoft Fabric Microsoft Cloud Tonya Swyers Microsoft 365 Microsoft Dynamics 365 ERP FABcon Google Cloud https://lnkd.in/ezMtj36q

#sharedUnifiedNamespace + Microsoft Fabric + AI: The Future of Smart Operations? As industrial data landscapes mature, the Unified Namespace (#UNS) is becoming the backbone of real-time, contextualized data across operations. Now, with Microsoft Fabric and AI entering the mix, we’re seeing a new frontier in industrial intelligence. Especially as Microsoft pushes MS Fabric into the market, we have many customer that work on this combination. Here’s a quick breakdown of the pros and cons of combining our #sharedUNS, Fabric and AI as I see them at the moment: ---------------------------------------------------------- Pros: Real-Time AI Insights: With UNS feeding live data into Fabric, AI models can generate predictive insights, detect anomalies, and optimize processes in real time. Unified Data Governance: MS Fabric’s OneLake architecture ensures secure, governed access to UNS data—ideal for training and deploying AI responsibly. Accelerated Decision-Making: AI- and Data-powered analytics in Fabric (via Copilot, Power BI, and Synapse) help teams move from data to decisions faster than ever. Low-Code AI Enablement: MS Fabric empowers developers to build AI-driven apps and workflows on top of UNS data—democratizing innovation. ---------------------------------------------------------- Cons: Integration Complexity: Aligning UNS topics with Fabric’s data models and AI pipelines requires careful architecture—especially in legacy environments. Even when you do not implement any AI-Use Case complexity is high and you need to do the right steps. Latency & Data Quality: AI models are only as good as the data they consume. Real-time ingestion must be optimized to avoid lag and ensure accuracy. Cost & Compute: AI workloads can be resource-intensive. Without proper governance, costs can escalate quickly. Skill Gaps: Bridging OT, IT, and AI expertise remains a challenge—especially when deploying advanced models in industrial settings. The combination of UNS, Microsoft Fabric, and AI holds massive potential—but success depends on thoughtful integration, strong governance, and cross-functional collaboration. If you have any questions how to start your journey pushing data from your shopfloor to MS Fabric, let's exchange! Transition Technologies PSC Germany Microsoft Fabric #ttpsc4industry #IndustrialAI #UnifiedNamespace #MicrosoftFabric #SmartFactory #DigitalTransformation #DataOps #PowerBI #IIoT #ManufacturingAnalytics #Copilot #AIinIndustry

The future of data and AI isn’t coming—it’s here. At #FabConVienna, Microsoft Fabric made it clear: the era of fragmented data is ending. With OneLake’s zero-copy mirroring, graph and geospatial capabilities, and developer-first extensibility, we’re moving toward a world where data is not just stored—it’s activated for AI at scale. This isn’t about features; it’s about strategy. Organizations that unify their data estate today will lead in building intelligent applications tomorrow. Question for you: How ready is your company data platform to power the next generation of AI-driven experiences? Read about all of the announcements made at FabCon Vienna here: https://lnkd.in/dmF_T5Uy #MicrosoftFabric #DataStrategy #AIInnovation