Listen free for 30 days
Listen with offer
-
Data Pipelines with Apache Airflow
- Narrated by: Julie Brierley
- Length: 10 hrs and 18 mins
Failed to add items
Add to basket failed.
Add to wishlist failed.
Remove from wishlist failed.
Adding to library failed
Follow podcast failed
Unfollow podcast failed
99p for the first 3 months
Data Pipelines with Apache Airflow
Buy Now for £18.99
No valid payment method on file.
We are sorry. We are not allowed to sell this product with the selected payment method
Listeners also enjoyed...
Summary
Data Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines.
Summary
A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, and keeping processes along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, this book teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack.
About the Technology
Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. Apache Airflow provides a single platform you can use to design, implement, monitor, and maintain your pipelines. It features easy-to-use UI, plug-and-play options, and flexible Python scripting.
About the Book
Data Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines. You’ll explore the most common usage patterns, including aggregating multiple data sources, connecting to and from data lakes, and cloud deployment. Part reference and part tutorial, this practical guide covers every aspect of the directed acyclic graphs (DAGs) that power Airflow, and how to customize them for your pipeline’s needs.
What's Inside
- Build, test, and deploy Airflow pipelines as DAGs
- Automate moving and transforming data
- Analyze historical datasets using backfilling
- Develop custom components
- Set up Airflow in production environments
About the Audience
For DevOps, data engineers, machine learning engineers, and sysadmins with intermediate Python skills.
About the Authors
Bas Harenslak and Julian de Ruiter are data engineers with extensive experience using Airflow to develop pipelines for major companies. Bas is also an Airflow committer.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.