Data Engineering on Microsoft Azure: The Serving Layer
Azure 2021
| Intermediate
- 11 Videos | 1h 4m 8s
- Includes Assessment
- Earns a Badge
Implementing an effective serving layer requires consideration for the design, methods, and tools. In this course, you'll learn how traditional relational models can be replaced by the star schema and how to design a star schema. Then, you'll explore the purpose and structure of Parquet files used by Azure Databricks. You'll learn how to design and query a dimensional hierarchy. You'll move on to examine Azure Synapse Analytics, including deploying dedicated SQL pools and Apache Spark clusters. Finally you'll learn how to create shared metadata tables between Spark clusters. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
WHAT YOU WILL LEARN
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discover the key concepts covered in this coursecompare the traditional relational schema model with the modern data lake star schemadescribe the steps required for modeling a star schemadefine what a Parquet file is and how it's structureddesign and query a dimensional hierarchydeploy an Azure Synapse Analytics workspace
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deploy an Azure Synapse Analytics Dedicated SQL pooldeploy an Azure Synapse Analytics Apache Spark cluster and attach a notebookdescribe how Azure Synapse Analytics shares databases between Spark clustersdeploy a shared database and a shared metadata tablesummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview1m 24sUP NEXT
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2.Relational and Star Schemas7m 14s
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3.Designing a Star Schema Database7m 17s
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4.Parquet Files4m 59s
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5.Dimensional Hierarchies11m 50s
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6.Deploying Azure Synapse Analytics4m 51s
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7.Deploying Azure Synapse Analytics Dedicated SQL Pools5m 56s
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8.Deploying Azure Synapse Analytics Apache Spark Clusters5m 56s
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9.Shared Metadata Tables5m 2s
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10.Implementing Shared Metadata Tables8m 44s
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11.Course Summary56s
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