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Data Engineering with Alteryx

You're reading from   Data Engineering with Alteryx Helping data engineers apply DataOps practices with Alteryx

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781803236483
Length 366 pages
Edition 1st Edition
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Author (1):
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Paul Houghton Paul Houghton
Author Profile Icon Paul Houghton
Paul Houghton
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Table of Contents (18) Chapters Close

Preface 1. Part 1: Introduction
2. Chapter 1: Getting Started with Alteryx FREE CHAPTER 3. Chapter 2: Data Engineering with Alteryx 4. Chapter 3: DataOps and Its Benefits 5. Part 2: Functional Steps in DataOps
6. Chapter 4: Sourcing the Data 7. Chapter 5: Data Processing and Transformations 8. Chapter 6: Destination Management 9. Chapter 7: Extracting Value 10. Chapter 8: Beginning Advanced Analytics 11. Part 3: Governance of DataOps
12. Chapter 9: Testing Workflows and Outputs 13. Chapter 10: Monitoring DataOps and Managing Changes 14. Chapter 11: Securing and Managing Access 15. Chapter 12: Making Data Easy to Use and Discoverable with Alteryx 16. Chapter 13: Conclusion 17. Other Books You May Enjoy

Summary

Now that we have our DataOps principles and understand how they work in the three pillars of People, Delivery, and Confidence, we learned the specifics of building a data pipeline with Alteryx and how to implement these principles.

The following section looked at the different processes for accessing data sources on the basis of the DataOps framework. Then, we learned how to transform those datasets with Alteryx and publish them in other storage locations. And finally, we used Alteryx to build reports and visualizations in value extraction processes.

In the next chapter, we will start by accessing internal data sources, whether those data sources are files or database connections. We will then look at how we can access external data sources, either open public or private secured data sources. Then we will look at some of the initial processes for making sure our sourced data is in a raw format for us to use.

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