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Data Engineering with Alteryx Helping data engineers apply DataOps practices with Alteryx

      Author: Baturi   |   09 July 2022   |   comments: 0

Data Engineering with Alteryx Helping data engineers apply DataOps practices with Alteryx
English | 2022 | ISBN: 1803236485 | 366 pages | True PDF EPUB | 30.84 MB
Build and deploy data pipelines with Alteryx by applying practical DataOps principles


Key Features
Learn DataOps principles to build data pipelines with Alteryx
Build robust data pipelines with Alteryx Designer
Use Alteryx Server and Alteryx Connect to share and deploy your data pipelines
Book Description
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.
What you will learn
Build a working pipeline to integrate an external data source
Develop monitoring processes for the pipeline example
Understand and apply DataOps principles to an Alteryx data pipeline
Gain skills for data engineering with the Alteryx software stack
Work with spatial analytics and machine learning techniques in an Alteryx workflow Explore Alteryx workflow deployment strategies using metadata validation and continuous integration
Organize content on Alteryx Server and secure user access
Who this book is for
If you're a data engineer, data scientist, or data analyst who wants to set up a reliable process for developing data pipelines using Alteryx, this book is for you. You'll also find this book useful if you are trying to make the development and deployment of datasets more robust by following the DataOps principles. Familiarity with Alteryx products will be helpful but is not necessary.



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