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Data Engineering with Alteryx

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

Product type Paperback

Published in Jun 2022

Publisher Packt

ISBN-13 9781803236483

Length 366 pages

Edition 1st Edition

Languages

C++

Tools

Alteryx

Concepts

Data Engineering

Author (1):

Paul Houghton

View More author details

Table of Contents (18) Chapters

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

Using Alteryx software with DataOps

The Alteryx platform components of Designer, Server, and Connect deliver the parts needed to support the DataOps framework pillars and fulfill the principles that make up those pillars. Each of the different software components fits across the People, Delivery, and Confidence pillars, serving the various functions needed to deliver in a DataOps framework.

In Figure 3.2, we have the same pillars from earlier, but with an overlay of where each Alteryx product interacts with the different pillars:

Figure 3.2 – DataOps pillars overlayed with the Alteryx products

In the diagram, we can see the three DataOps principles and how Designer supports the People and Delivery pillars, Connect enables the Confidence pillar, while Server supports the principles across all pillars.

Alteryx Designer

Building a DataOps pipeline will always start with development in Alteryx Designer. First, the quick iteration that I have been...

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Authors (1)

Paul Houghton

Paul Houghton

Paul Houghton is an experienced business analyst with the ability to make focused data-led decisions. He is able to utilize data from a multitude of sources, including structured company data alongside unstructured data, such as social media sites. Paul's ability to combine data from structured business sources with open and unstructured data and analyze a range of datasets enables him to make fast, accurate, and relevant business decisions.

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