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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

Chapter 2: Data Engineering with Alteryx

In Chapter 1, Getting Started with Alteryx, we began exploring the Alteryx platform and its use in data engineering. In this chapter, we will examine what the role of data engineering involves and how a person in that role would use the Alteryx platform. Throughout this book, we will assume you have a solid understanding of analytical processes but don't have any experience with Alteryx to deliver end-to-end analytic datasets. We will also learn about the DataOps framework and how an Alteryx data engineer can use it.

We will cover the following topics in this chapter:

What is a data engineer?
Using Alteryx products as a data engineer
Applying DataOps as an Alteryx data engineer

The rest of the chapter is locked

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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.

See other products by Paul Houghton

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