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Data Engineering with Alteryx

Data Engineering with Alteryx

By : Paul Houghton
4.8 (11)
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Data Engineering with Alteryx

Data Engineering with Alteryx

4.8 (11)
By: Paul Houghton

Overview of this book

Alteryx is a GUI-based development platform for data analytic applications. Data Engineering with Alteryx will help you leverage Alteryx’s code-free aspects which increase development speed while still enabling you to make the most of the code-based skills you have. This book will teach you the principles of DataOps and how they can be used with the Alteryx software stack. You’ll build data pipelines with Alteryx Designer and incorporate the error handling and data validation needed for reliable datasets. Next, you’ll take the data pipeline from raw data, transform it into a robust dataset, and publish it to Alteryx Server following a continuous integration process. By the end of this Alteryx book, you’ll be able to build systems for validating datasets, monitoring workflow performance, managing access, and promoting the use of your data sources.
Table of Contents (18 chapters)
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1
Part 1: Introduction
5
Part 2: Functional Steps in DataOps
11
Part 3: Governance of DataOps

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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Data Engineering with Alteryx
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