Data Ingestion with Python Cookbook. A practical guide to ingesting, monitoring, and identifying errors in the data ingestion process Rydułtowy

Data Ingestion with Python Cookbook offers a practical approach to designing and implementing data ingestion pipelines. It presents real-world examples with the most widely recognized open source tools on the market to answer commonly asked questions and overcome challenges.You’ll be introduced to designing and working with or without data schemas, as well as creating monitored pipelines with Airflow and data observability principles, all while following industry best practices. The book also addresses challenges associated with reading different data sources and data formats. As you progress through the book, you’ll gain a broader understanding of error logging best practices, troubleshooting techniques, data orchestration, monitoring, and storing logs for further consultation.By the end of the book, you’ll have a fully automated set that enables you to start ingesting and monitoring your data pipeline effortlessly, facilitating seamless integration with subsequent stages of the ETL process. Spis treści: 0. PI1. Introduction to Data Ingestion2. Principals of Data Access – Accessing your Data3. Data Discovery – Understanding Our Data Before Ingesting It4. Reading CSV and JSON Files and Solving Problems5. Ingesting Data from Structured and Unstructured Databases6. Using PySpark with Defined and Non-Defined Schemas7. Ingesting Analytical Data8. Designing Monitored Data Workflows9. Putting Everything Together with Airflow10. Logging and Monitoring Your Data Ingest in Airflow11. Automating Your Data Ingestion Pipelines12. Using Data Observability for Debugging, Error Handling, and Preventing Downtime