ETL Strategies in Microsoft Fabric - Pipelines, Dataflows & Notebooks

🎯 The Problem: Your ETL jobs take 6 hours. Business users want data “as fresh as possible.” You’re juggling Dataflows, Notebooks, Pipelines, and now Mirroring - but which one is actually right for which scenario?

💡 This Evening: We’ll cut through the confusion with a clear decision framework. You’ll see each tool in action and understand when to use Spark vs. Dataflows vs. Mirroring - with real-world examples.

⏱️ Save yourself: Weeks of painful refactoring. Choose the right ETL approach from day one.

What you’ll learn

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• ⚙️ Spark Environments – Managing libraries and configurations, and WHY environment isolation matters for production
• 🚀 Spark Job Definitions – Automating Spark jobs at scale, and WHY scheduled jobs beat manual notebook runs
• 🔄 Data Factory Pipelines – Enterprise orchestration with activities, and WHY Fabric Pipelines are simpler than classic ADF
• 🪞 Database Mirroring – Near real-time replication from SQL Server, Cosmos DB, Snowflake, and WHY mirroring beats traditional CDC approaches

Agenda

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Who should attend

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Data Engineers building ETL pipelines, DBAs managing data integration, Architects designing data platforms.

Part of the monthly Fabric Meetup Series by The Trusted Advisor.