
- 366 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Data Engineering with Alteryx
About this book
Build and deploy data pipelines with Alteryx by applying practical DataOps principlesKey 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 pipelinesBook DescriptionAlteryx 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 accessWho this book is forIf 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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Table of contents
- Data Engineering with Alteryx
- Contributors
- Preface
- Part 1: Introduction
- Chapter 1: Getting Started with Alteryx
- Chapter 2: Data Engineering with Alteryx
- Chapter 3: DataOps and Its Benefits
- Part 2: Functional Steps in DataOps
- Chapter 4: Sourcing the Data
- Chapter 5: Data Processing and Transformations
- Chapter 6: Destination Management
- Chapter 7: Extracting Value
- Chapter 8: Beginning Advanced Analytics
- Part 3: Governance of DataOps
- Chapter 9: Testing Workflows and Outputs
- Chapter 10: Monitoring DataOps and Managing Changes
- Chapter 11: Securing and Managing Access
- Chapter 12: Making Data Easy to Use and Discoverable with Alteryx
- Chapter 13: Conclusion
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