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Medallion Architecture in Practice

In this video, Carmel Eve dives deep into the medallion architecture's semantic layer and answer the critical question: when is your data truly production-ready? Building on our previous introduction to the medallion architecture, this video covers: ⏱️ TIMESTAMPS: 00:00 Introduction and Recap 00:06 Understanding the Semantic Layer 01:21 Defining the Semantic Layer 03:02 Data Production Readiness 03:13 Development, Testing, and Production Environments 04:43 Applying the Medallion Architecture 09:30 Conclusion and Key Takeaways 📊 KEY TOPICS COVERED: ✅ How the semantic layer adds context to your gold layer data ✅ Differences between gold layer and semantic layer ✅ Real-world examples using Power BI, Microsoft Purview & Databricks Unity Catalog ✅ Understanding data products and versioning ✅ Multi-environment deployment strategies for data ✅ When silver tier data is production-ready (hint: it's not just gold!) ✅ Best practices for implementing medallion architecture 🔑 MAIN TAKEAWAYS: The semantic layer is NOT the same as the gold layer Production-ready data exists in BOTH silver and gold tiers (in production environment) Data quality doesn't automatically improve through tiers - it's about opinionation Multi-environment approach is crucial for reliable data architecture 💡 WHO THIS VIDEO IS FOR: Data Engineers implementing lakehouse architectures Data Architects designing modern data platforms Analytics Engineers working with medallion patterns Anyone building production data pipelines on Azure, Databricks, or similar platforms #MedallionArchitecture #DataEngineering #SemanticLayer #Lakehouse #DataArchitecture #ProductionData #AzureDataFactory #Databricks #PowerBI #DataLake #BigData #ModernDataStack #DataPlatform #CloudArchitecture #DataOps