Book Image

Data Engineering with Alteryx

By : Paul Houghton
Book Image

Data Engineering with Alteryx

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)
Part 1: Introduction
Part 2: Functional Steps in DataOps
Part 3: Governance of DataOps

Chapter 3: DataOps and Its Benefits

In Chapter 2, Data Engineering with Alteryx, we introduced Alteryx products, the DataOps framework, and how Alteryx products are accommodated within the DataOps framework. This chapter will look at the key benefits of applying DataOps and what rewards you will gain by implementing DataOps in your organization.

We will explore the principles of DataOps and investigate how they apply to Alteryx development. We will also look at the specifics of which tools in the Alteryx platform can implement the principles of DataOps.

Throughout this chapter, you will learn how Alteryx can help leverage the DataOps process and apply the principles in an Alteryx pipeline.

In this chapter, we will cover the following topics:

  • The benefits the DataOps framework brings to your organization
  • Understanding DataOps principles
  • Applying DataOps to Alteryx
  • Using Alteryx software with DataOps
  • General steps for deploying DataOps in your environment...