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Data Ingestion with Python Cookbook

Data Ingestion with Python Cookbook

By : Gláucia Esppenchutz
4.5 (4)
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Data Ingestion with Python Cookbook

Data Ingestion with Python Cookbook

4.5 (4)
By: Gláucia Esppenchutz

Overview of this book

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.
Table of Contents (17 chapters)
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1
Part 1: Fundamentals of Data Ingestion
9
Part 2: Structuring the Ingestion Pipeline

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

Symbols

.options() configurations 112-114

reference link 114

A

access control

for databases 38

for data warehouses 38

Access Control Lists (ACLs) 63

reference link 70

accessibility 32

ACL policy 70

Administrator role 84

advanced monitoring

counters 306

designing 304-309

gauges 306

Grafana 308

Prometheus 308

StatsD 307

timers 306

Airflow 63, 326

basic logs, creating 283-288

configuring 244-248

connectors, creating 265-269

Docker, configuring for 16-21

environment variables, in docker-compose 282, 283

installing 244, 282, 326

reference link 22, 331

running 282, 326

Airflow architecture

celery 305

relational database 305

scheduler 305

web server 305

workers 305

airflow.cfg

exploring 302...

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