Data Engineering with Alteryx: Helping data engineers apply DataOps practices with Alteryx
Category
Author
Publication
Packt Publishing
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.
Review
"Whether you are new to Alteryx, a seasoned Alteryx developer or looking to improve the governance and control of workflows, with this book, youll join Paul as he shares his in-depth knowledge of the Alteryx platform and the core principles of data engineering, resulting in you building and maintaining better workflows."
Chris Goodman, Alteryx ACE and Director - Alteryx Community of Practice at PwC UK
"This excellent book will teach you many different DevOps practices that you can apply in Alteryx.
Paul Houghton (the author) has robust experience in the Alteryx field as he has been an Alteryx consultant for several years. Paul did a great job explaining the DevOps process, and I believe many advanced users will find this book to be a great source of knowledge.
So, who should read this book? I strongly recommend this book to people who use Alteryx daily and want to go to another level."
Emil Kos, Alteryx ACE Alteryx consultant and trainer at Data Pal
About the Author
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.
- 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
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.
- Getting Started with Alteryx
- Data Engineering with Alteryx
- DataOps and Its Benefits
- Sourcing the Data
- Data Processing and Transformations
- Destination Management
- Extracting Value
- Beginning Advanced Analytics
- Testing Workflows and Outputs
- Monitoring DataOps and Managing Changes
- Securing and Managing Access
- Making Data Easy to Use and Discoverable with Alteryx
- Conclusion
