DP-203: Processing in Azure Using Batch Solutions

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Chris Behrens

7:05:47

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01 Introduction

001 Course Introduction.mp4

02:26

002 Setting Up the Environment.mp4

07:42

02 Develop a Batch Processing Solution

001 Section Introduction.mp4

01:44

002 Identifying Azure Services for Batch Processing.mp4

10:40

003 Developing a Batch Processing Solution with Azure Synapse Analytics.mp4

14:13

004 Introducing Dedicated SQL Pool.mp4

11:49

004 Memory and Concurrency Limits for Dedicated SQL Pool in Azure Synapse Analytics.txt

005 Introducing PolyBase.mp4

06:05

006 Demo Using PolyBase to Load Data to Dedicated SQL Pool.mp4

11:45

006 GitHub link to Demo Files.txt

008 Introducing Azure Synapse Link (HTAP Solutions and Cosmos DB).mp4

05:41

009 Demo Implementing Azure Synapse Link for Cosmos DB and Querying the Replicated Data.mp4

08:13

009 GitHub link to Demo Files.txt

010 Creating Data Pipelines Using Synapse Pipelines and Data Factory.mp4

14:55

010 GitHub link to Demo Files.txt

012 Creating Tests for Data Pipelines.mp4

06:14

013 GitHub link to Demo Files.txt

013 Integrating JupyterPython Notebooks into a Data Pipeline.mp4

14:28

014 GitHub link to Demo Files.txt

014 Introducing Mapping Data Flows in Synapse Pipelines and Data Factory.mp4

12:35

015 Introducing Inserts Upserts and Updates.mp4

07:03

016 Demo Upserting Data in Azure Synapse Analytics Part 1.mp4

08:32

016 GitHub link to Demo Files.txt

017 Demo Upserting Data in Azure Synapse Analytics Part 2.mp4

08:04

017 GitHub link to Demo Files.txt

019 GitHub link to Demo Files.txt

019 Introducing Activity Dependencies in Synapse Pipelines and Data Factory.mp4

07:08

020 Configuring Exception Handling in Synapse Pipelines and Data Factory.mp4

06:43

021 GitHub link to Demo Files.txt

021 Introducing Integration Runtime in Synapse Pipelines and Data Factory.mp4

13:13

022 Using Self-Hosted Integration Runtime to Copy Data from On-Premises Data Source.mp4

09:35

023 Reverting Data to a Previous State in Azure Storage.mp4

11:33

024 Reverting Data to a Previous State in Azure SQL and Dedicated SQL Pool Databases.mp4

11:08

025 Introducing Azure Databricks.mp4

10:39

026 GitHub link to Demo Files.txt

026 Setting Up Azure Databricks Workspace.mp4

13:43

027 Building a Data Pipeline Using Azure Databricks.mp4

11:53

027 GitHub link to Demo Files.txt

028 GitHub link to Demo Files.txt

028 Integrating Databricks with Synapse Pipelines and Data Factory.mp4

05:52

029 Introducing Delta Lake with Azure Databricks Part 1.mp4

08:36

030 Introducing Delta Lake with Azure Databricks Part 2.mp4

13:53

031 GitHub link to Demo Files.txt

031 Read from and Write to Delta Lake Part 1.mp4

11:04

032 GitHub link to Demo Files.txt

032 Read from and Write to Delta Lake Part 2.mp4

13:50

033 Memory and Concurrency Limits for Dedicated SQL Pool in Azure Synapse Analytics.txt

033 Scale Azure SQL and Dedicated SQL Pool Databases.mp4

07:37

034 Section Recap.mp4

11:45

03 Manage Batches and Pipelines

001 Section Introduction.mp4

01:22

002 Introducing Azure Batch.mp4

05:17

003 Demo Processing Data with Azure Batch.mp4

09:27

003 GitHub link to Demo Files.txt

004 Handle Failed Batch Loads for Azure Batch.mp4

08:08

005 Validate Batch Loads for Azure Batch.mp4

06:44

006 Configure Batch Retention for Azure Batch.mp4

03:30

006 GitHub link to Demo Files.txt

007 GitHub link to Demo Files.txt

007 Trigger Azure Batch with Synapse Pipelines and Data Factory.mp4

08:26

008 GitHub link to Demo Files.txt

008 Manage Data Pipelines with Synapse Pipelines and Data Factory.mp4

05:41

009 Introducing Windows.mp4

05:49

010 Schedule Data Pipelines in Synapse Pipelines and Data Factory.mp4

09:58

011 GitHub link to Demo Files.txt

011 Manage Spark Jobs in a Pipeline.mp4

05:43

012 Introducing Git and GitHub.mp4

08:07

013 Implement Version Control for Pipeline Artifacts.mp4

08:51

015 Section Recap.mp4

05:22

04 Conclusion

001 Course Summary.mp4

06:41

002 Conclusion and Whats Next.mp4

01:30

003 Exam Guide.mp4

04:50

Description

You'll prepare for the Azure DP-203 exam by learning how to develop and manage end-to-end batch processing solutions using Azure services.

What You'll Learn?

The recommended order of courses to prepare for the DP-203: Data Engineering on Microsoft Azure certification is as follows: * Building an Azure Data Engineer Foundation * Data Ingestion and Preparation * Processing in Azure Using Batch Solutions * Processing in Azure Using Streaming Solutions * Secure, Monitor, and Optimize Data Storage and Processing Finally, use the practice exams to test your understanding for the exam. In this course, *DP-203: Processing in Azure Using Batch Solutions*, you’ll learn to work with various Azure Data services to build end-to-end batch processing solutions. First, you’ll explore the different data services available in Azure that can be used for batch pipelines. Next, you’ll see how to extract data using Azure Synapse and Data Factory. Then, you’ll learn how to build pipelines by copying data, performing upserts, and handling dependencies and errors. Following this, you’ll see how to process data with Azure Databricks and Delta Lake. Finally, you’ll learn how to work with Azure Batch and manage data pipelines. When you’re finished with this course, you’ll have the skills and knowledge of Azure Data services needed to build batch processing solutions.

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Microsoft Azure

Chris Behrens

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