Azure Data Factory

44mIntermediate2023-01-19

Authors

Karsten Ulferts

Helping companies integrate cloud computing into their IT strategies

Course details

If you want to grow your skills as a data scientist or enterprise application expert, you need to know how to design and manage an integrated IT strategy. Enter Azure Data Factory, the fully managed, serverless data integration service from Microsoft. In this course, instructor Karsten Ulferts shows you how to use Azure Data Factory (ADF) for pipelining and data transformation.

Explore the basics of successful deployment and the key terms of the ADF object model, ramping up your skill set to assess and analyze data output and data quality. Learn how concrete data integration solutions can be implemented with ADF, using extensions and available improvements to go beyond normal testing operations. Karsten gives you tips along the way on other more advanced object modeling tools, such as triggers, integration runtimes, Power Query, flowlets, quotas, limitations, and more.

Skills covered

Data GovernanceData EngineeringAzureLearningData ScienceMicrosoft

Concepts

0. Introduction

01 - Pipelining data with Azure Data Factory
02 - What you should already know

1. Azure Data Factory (ADF) Deployment

03 - Deployment using Azure Portal
04 - Taking a look at an ADF instance
05 - ADF studio

2. Understanding ADF Basic Object Model

06 - ADF basic object model
07 - Preparing for your first data ingestion
08 - Configure your first simple data copy solution
09 - Data copy pipeline results
10 - Review object model and clean-up

3. Data Transformation

11 - Data flow
12 - Filtering data
13 - Debugging
14 - Orchestration

4. Understanding ADF Advanced Object Model

15 - Triggers
16 - Integration runtime
17 - Power Query
18 - Flowlet
19 - Quotas and limitations

Conclusion

20 - Next steps