Data Engineering with Alteryx
Helping data engineers apply DataOps practices with Alteryx
Created by Paul Houghton
Explore how to build reliable and efficient data pipelines using Alteryx and DataOps principles. You'll learn to transform raw data into valuable datasets and manage workflows that are both robust and scalable. Gain practical skills to streamline data engineering tasks and improve data quality.
Packt | Jun 2022 | 366 min
What You Will Learn
You'll progress through practical sections that guide you from building basic pipelines to implementing advanced monitoring and deployment strategies. Each section focuses on real-world scenarios, helping you apply DataOps concepts directly within Alteryx. By the end, you'll have hands-on experience creating, validating, and managing data workflows.
Key Features
- Apply DataOps principles to automate and optimize Alteryx workflows
- Design, validate, and monitor robust data pipelines for reliable datasets
- Deploy and manage workflows on Alteryx Server for secure data sharing
Target Audience
Ideal for data engineers, data scientists, and analysts looking to develop or improve data pipelines using Alteryx. If you want to make your data processes more reliable and efficient by applying DataOps practices, you'll benefit from these step-by-step instructions. Some familiarity with Alteryx is helpful but not required.
