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Hey data engineers! We've finished transforming our data - it's now pure, pristine, and ready to be consumed as facts and dimensions. Great! The only issue is that it's located in a data lake using the delta format, and not every consumer can connect to it. Or maybe we just prefer a good, old-fashioned, traditional relational data warehouse instead of this "data lake thing." What should we do? How can we make it work? Fortunately, Azure Synapse Analytics has a component that can be used as a "relational" data warehouse: the Dedicated SQL Pool. Join me in the 43rd episode of my free DP-203 course, where I'll present an overview of the Dedicated SQL Pool, explain how to integrate it into our design, and discuss its architecture. Enjoy! ▬▬▬▬▬▬ IMPORTANT LINKS ▬▬▬▬▬▬ My LinkedIn profile: https://www.linkedin.com/in/piotr-tybulewicz-81a8793/ GitHub with my drawings: https://github.com/TybulOnAzure/DP-203 ▬▬▬▬▬▬ MEMBERSHIP ▬▬▬▬▬▬ Join this channel to get access to perks: https://www.youtube.com/channel/UCLnXq-Fr-6rAsCitq9nYiGg/join ▬▬▬▬▬▬ CHAPTERS ▬▬▬▬▬▬ 00:00 Introduction 01:29 Synapse components 04:44 Where does it fit? 12:22 Architecture of Dedicated SQL Pool 26:50 Performance levels 30:18 Creating Dedicated SQL Pool 36:54 Hash distributed tables 55:34 Create a hash distributed table 58:36 Round-robin distribution 1:06:17 Replicated tables 1:11:04 Summary
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