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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: / piotr-tybulewicz-81a8793
GitHub with my drawings: github.com/TybulOnAzure/DP-203
▬▬▬▬▬▬ MEMBERSHIP ▬▬▬▬▬▬
Join this channel to get access to perks:
/ @tybulonazure
▬▬▬▬▬▬ 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