Hello Tech Enthusiasts, I’m excited to invite you to today’s meetup (October 23, 2025) at 20:00 Baku time (GMT+4) , where Victoria Eshelby from Microsoft Netherlands will be our guest speaker. She’ll present “Intelligent Pipelines in Action: AI Collaboration with Fabric,” exploring how Fabric enables smarter, end-to-end AI-powered data solutions. 👉 Register now to join: https://www.meetup.com/azerbaijanpowerbi-microsoftfabriccommunity/events/311254306/?eventOrigin=group_upcoming_events I look forward to seeing you there!
🎙️ Excited to share that today I had the opportunity to moderate a DP-700 Exam Study Session on “Monitor and Optimize Solutions” — organized by Microsoft Reactor! Together with my colleague Amit Chandak, we answered attendee questions about performance optimization, data monitoring, and solution tuning in Microsoft Fabric and Power BI — key concepts for anyone preparing for the DP-700: Designing and Implementing Microsoft Fabric Analytics Solutions exam. It’s always inspiring to see professionals from around the world engage, share insights, and strengthen their learning journey toward certification. #DP700 #MicrosoftFabric #PowerBI #MicrosoftReactor #DataPlatform #FabricCommunity #MVPBuzz #MCT #IlgarZarbaliyev #LearningNeverStops #MicrosoftCertification #DataAnalytics
🚀 Replay Available! DP-600 Lab – Ingest Data with a Pipeline in Microsoft Fabric I’ve just delivered another hands-on DP-600 lab session — this time focused on Ingest Data with a Pipeline in Microsoft Fabric — and the full recording is now available to watch! If you're building skills for the Fabric Analytics Engineer Associate certification or want to understand real-world data ingestion patterns in Fabric, this session is packed with practical insights. In this lab, we walk through how to build a complete data ingestion workflow using Data Pipelines and Apache Spark , moving data from operational sources into OneLake , processing it, and preparing it for analysis in your Lakehouse. 🔍 What You’ll Learn: • How data ingestion pipelines work in Microsoft Fabric • Building ETL/ELT processes to load data into a Lakehouse • Using Apache Spark for scalable data transformations • End-to-end workflows combining Pipelines + Spark • Preparing structured, analysis-ready data in F...
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