End-To-End Microsoft Fabric Data Engineering Project | Metadata Driven Bulk Load Pipeline
Welcome to Part 2 of the End-to-End Microsoft Fabric Data Engineering Project series.
In this video, we build a Metadata-Driven Bulk Load Pipeline to ingest multiple tables from an On-Prem SQL Server into the Bronze Layer (Raw Lakehouse) in Microsoft Fabric.
This is a real-world enterprise Data Engineering approach where we dynamically load source tables into the Raw Layer using reusable pipeline logic.
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🎯 What you’ll learn in this video:
✔ Connecting On-Prem SQL Server to Microsoft Fabric
✔ Understanding Metadata-Driven Pipelines
✔ Bulk loading multiple tables dynamically
✔ Loading data into Bronze Layer (Raw_LH)
✔ Creating scalable ingestion architecture
✔ Enterprise Medallion Architecture approach
✔ Reusable Fabric pipeline design
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📂 Tables Loaded into Bronze Layer:
✔ raw_Customers
✔ raw_Products
✔ raw_Orders
✔ raw_Employees
✔ raw_OrderItems
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🏗️ Architecture Covered:
On-Prem SQL Server
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Metadata-Driven Fabric Pipeline
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Bronze Layer (Raw Lakehouse)
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🧠 Why Metadata-Driven Pipelines?
Instead of creating separate pipelines for every table, we use metadata to create scalable and reusable ingestion logic.
Benefits:
• Reduced development effort
• Easy maintenance
• Scalable ingestion
• Enterprise-ready architecture
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👥 Who should watch this?
• Microsoft Fabric learners
• Data Engineers
• ETL developers
• Azure Data Factory professionals
• Interview preparation candidates
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📅 Upcoming Videos:
▶ Silver Layer transformations
▶ Dataflow Gen2 implementation
▶ Incremental loading
▶ Warehouse loading
▶ Semantic model & Power BI reporting
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🔔 Subscribe for the full Microsoft Fabric Data Engineering Project series
👍 Like if metadata-driven pipelines are clear now
💬 Comment “Part 3” if you’re ready for Silver Layer transformations
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