Data Ingestion with Python Cookbook
A practical guide to ingesting, monitoring, and identifying errors in the data ingestion process
Created by Gláucia Esppenchutz
Explore practical techniques for building and managing data ingestion pipelines using Python and popular open source tools. Learn how to handle data from various sources, automate workflows, and monitor for errors to ensure smooth and reliable data movement. Gain hands-on experience with real-world scenarios and industry best practices.
Packt | May 2023 | 414 min
What You Will Learn
You will work through practical, step-by-step examples that guide you in designing, automating, and monitoring data ingestion workflows. By applying proven techniques with tools like PySpark and Airflow, you will learn how to troubleshoot issues, implement data observability, and ensure your pipelines are resilient and efficient.
Key Features
- Develop robust data ingestion pipelines with Python and PySpark
- Automate and orchestrate workflows using Apache Airflow
- Integrate monitoring and observability to catch and resolve errors early
Target Audience
Ideal for data engineers and technical professionals with some experience in Python who want to deepen their skills in data ingestion. If you are looking to automate, monitor, and improve your data pipelines using open source tools, this course will help you build confidence and expertise in real-world data engineering tasks.
