Best Microsoft Fabric Training in Bangalore | Online Visualpath

1. The Next Evolution of Data Engineering with Microsoft Fabric

2. Introduction to Microsoft Fabric • Unified, end-to-end analytics platform built for modern enterprises • Combines data engineering, BI, data science, and real-time analytics • Eliminates complexity by integrating multiple Azure data services • Offers consistent user experience through a single SaaS interface • Designed for scalability, governed data access, and faster insights

3. Key Components of Microsoft Fabric • Lakehouse architecture powered by OneLake • Data Factory for pipelines and data movement • Synapse Data Engineering & Data Warehousing • Real-Time Analytics for streaming and event processing • Power BI for visualization and business insights

4. OneLake – The Foundation of Fabric • Acts as a single, unified data lake for the entire organization • Removes data silos by centralizing all storage • Supports open-format Delta Lake tables • Enables cross-workload data sharing without duplication • Provides unified governance and compliance controls

5. Why Fabric is Transforming Data Engineering • Simplifies architecture with an all-in-one analytics ecosystem • Lowers operational cost by reducing separate tools and storage • Boosts productivity with a no-copy data model • Enhances collaboration among analysts, engineers, and scientists • Enables faster data-to-insight workflows

6. Data Engineering in Fabric • Code-first and low-code data transformation with notebooks & pipelines • Auto-scale Spark environments for heavy processing • Seamless integration with real-time and batch data workloads • Robust DevOps, versioning, and Git integration • Reusable models with dataflows and semantic models

7. Real-Time Analytics in Fabric • Handles high-speed streaming data from apps, IoT, and logs • Uses KQL database engine for fast processing • Supports operational dashboards with near-live metrics • Easily merges real-time with historical insights • Allows real-time anomaly detection and alerting

8. Real-Time Analytics in Fabric • Handles high-speed streaming data from apps, IoT, and logs • Uses KQL database engine for fast processing • Supports operational dashboards with near-live metrics • Easily merges real-time with historical insights • Allows real-time anomaly detection and alerting

9. The Future of Data Engineering with Fabric • Convergence of all analytics workloads into a single experience • AI-powered automation for pipeline and model optimization • Enhanced governance with unified data catalogs • Greater support for hybrid and multi-cloud scenarios • Accelerated decision-making with real-time intelligence

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