This course helps you master Azure Data Factory, build scalable pipelines, integrate data, orchestrate workflows, and excel in data engineering roles.

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Azure has become a leading cloud platform. Expertise in ADF opens doors to lucrative roles in data engineering and analytics.

This course provides you with the essential skills to master Azure Data Factory. You’ll start with ADF’s core concepts, architecture, and data connectivity to both on-premises and cloud sources. Through hands-on lessons and real-world examples, you’ll learn to create, manage, and monitor pipelines, handle incremental data loads, and work with version control using Git. Advanced topics include big data integration with Azure SQL, HDInsight, and Hive and designing analytics and machine learning workflows.

After completing this course, you’ll confidently design, develop, and maintain data pipelines in Azure Data Factory. You’ll be equipped to tackle integration challenges, optimize cost and performance, ensure scalability and high availability, and implement data governance and security—boosting your career prospects in data engineering and analytics.

Azure Data Factory Bootcamp: From Beginner to Expert

To make data pipeline design more complex

To improve the scalability and high availability of ADF

To provide a common framework for solving common design problems in ADF

What is the primary purpose of design patterns in ADF?

What is the primary purpose of design patterns in ADF?

Specifies the Azure region for capacity reservation

Specifies the SKU for which the capacity reservation is being created

Specifies the new desired capacity for the capacity reservation

Specifies the name of the capacity reservation group

What is the purpose of the `--capacity` parameter in the Azure CLI command when creating a capacity reservation?

What is the purpose of the <code>--capacity</code> parameter in the Azure CLI command when creating a capacity reservation?

    az capacity reservation group create


Which Azure CLI command is used to create a new capacity reservation group?

Which Azure CLI command is used to create a new capacity reservation group?

It creates a capacity reservation for 5 instances of the `Standard_A1_v2` VM SKU in the `eastus` region, within the resource group `scalingRG`, under the capacity reservation group `skuReservationGroup`, with the reservation named `skuReservationName`.

It initiates the deletion of a capacity reservation group named `skuReservationGroup` in the `scalingRG` resource group.

This command has incorrect syntax and will result in an error.

It updates the capacity reservation named `skuReservationName` within the `scalingRG` resource group to increase its capacity to `5`.

Which option correctly describes the purpose of the given Azure CLI command?

    az capacity reservation create -c "skuReservationGroup" -n "skuReservationName" -l eastus -g "scalingRG"  --sku Standard_A1_v2 --capacity 5

Which option correctly describes the purpose of the given Azure CLI command?
<pre><code>az capacity reservation create -c &quot;skuReservationGroup&quot; -n &quot;skuReservationName&quot; -l eastus -g &quot;scalingRG&quot; --sku Standard_A1_v2 --capacity 5</code></pre>

    az capacity reservation update -c "skuReservationGroup" -n "skuReservationName" -g "scalingRG" --new-capacity 10

    az reservation update -c "skuReservationGroup" -n "skuReservationName" -g "scalingRG" --capacity 10

    az capacity reservation update --new-capacity 8 -c "newReservationGroup" -n "newReservationName" -g "newScalingRG"

    az capacity reservation update -c "skuReservationGroup" -n "skuReservationName" --capacity 15

Which Azure CLI command is used to update a capacity reservation group?

Which Azure CLI command is used to update a capacity reservation group?

Horizontal scaling increases the number of nodes in a cluster, while vertical scaling increases the resources of each node.

Horizontal scaling is best suited for scenarios where a single node cannot handle the load, while vertical scaling is best suited for scenarios where a single node is sufficient but requires more resources.

Horizontal scaling can be achieved by increasing the number of data integration runtimes (DIRs) in ADF, while vertical scaling can be achieved by upgrading the compute size of the existing DIRs.

Both horizontal and vertical scaling can be achieved using Azure CLI commands.

**(Select all that apply.)**
Which statement about horizontal and vertical scaling in Azure Data Factory (ADF) is *true*? 

(Select all that apply.)
Which statement about horizontal and vertical scaling in Azure Data Factory (ADF) is true?

Test your understanding of best practices for optimizing your usage of Azure resources.

Getting Started

Introduction to Azure Data Factory

Setting Up an Azure Data Factory Environment

Data Connectivity and Management

Azure Data Factory: Introduction and Connectivity Exam

Creating Data Pipelines in Azure Data Factory

Managing and Monitoring Azure Data Factory Pipelines

Azure Data Factory: Designing and Maintaining Data Pipelines Exam

Big Data Integration and Processing

Machine Learning and Advanced Analytics

Azure Data Factory: Big Data Processing and Machine Learning Exam

Data Governance and Security

Azure Data Factory: Best Practices

Conclusion

Appendix

Quiz: Azure Data Factory Best Practices