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Data Engineering with Alteryx
Data Engineering with Alteryx

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

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Key benefits

  • 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

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.

Who is this book 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.

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 30, 2022
Length: 366 pages
Edition : 1st
Language : English
ISBN-13 : 9781803231983
Vendor :
Alteryx
Category :
Languages :
Tools :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
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Product feature icon AI Assistant (beta) to help accelerate your learning
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Product Details

Publication date : Jun 30, 2022
Length: 366 pages
Edition : 1st
Language : English
ISBN-13 : 9781803231983
Vendor :
Alteryx
Category :
Languages :
Tools :

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Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(11 Ratings)
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4 star 18.2%
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sandee matecko Jul 30, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Best practices, tips and tricks, and more- this book is great for any level, from beginner to expert!
Amazon Verified review Amazon
Patrick H Aug 19, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book provides a little bit of everything for all skill levels of Alteryx users. It will guide you through creating your first workflow if you are brand new to the tool to advanced concepts like administrating Alteryx Server, which I found particularly useful, and DataOps concepts. I highly recommend this book for anyone who wants to level up their Alteryx skills!
Amazon Verified review Amazon
Albert Bellamy Jul 15, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The media could not be loaded. Just what the heck is Data Engineering anyway?Crack open this book and you'll find out.I recently finished "Data Engineering with Alteryx" by Paul Houghton, published by #Packt.This book outlines how to take your data from zero to hero with Alteryx and other platforms:1. Input of data from external sources, databases and APIs to other source systems2. Repeatable processes in #Alteryx like data cleansing, ETL, data profiling, and transformation,3. Output to destinations, whether that's a database management system like #Snowflake, a BI platform like #Tableau, or using Alteryx's underrated system of generated automated reports and visualizations on prem.The book presents these processes through the lens of the DataOps process, and uses that process to prescribe best practices for management of the data itself as well as workflows that can get a bit messy in a team environment.This isn't a catch-all book for beginners, spelling out how to use basic Alteryx functions.If you need that, go to the Alteryx community. The Core cert training path will take you right up to the point where this book will be tremendously useful to you.Highly recommend this book as a guideline to operationalize your use of Alteryx and Alteryx Server!
Amazon Verified review Amazon
JF Jul 03, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have been reviewing the new book "Data Engineering with Alteryx " by Paul Houghton and have thoroughly enjoyed it!This book will help data professionals early in their careers to understand the DataOps principles and how they can use them in Alteryx to build data pipelines. It will also guide Alteryx workflow deployment strategies.Experienced data engineers can leverage this book to get insights into advanced analytical techniques like spatial analytics and machine learning!There is also valuable content about managing Alteryx servers and user access. This book is a vital tool in the data engineer's toolbox!
Amazon Verified review Amazon
Dominika Kwiatkowska Oct 03, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I bought kindle version and it's so useful with links and samples of workflowsGreat for dataops framework and establishing data engineering path in the analytics team
Amazon Verified review Amazon
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