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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

Preface

Welcome to Data Ingestion with Python Cookbook. I hope you are excited as me to enter the world of data engineering.

Data Ingestion with Python Cookbook is a practical guide that will empower you to design and implement efficient data ingestion pipelines. With real-world examples and renowned open-source tools, this book addresses your queries and hurdles head-on.

Beginning with designing pipelines, you’ll explore working with and without data schemas, constructing monitored workflows using Airflow, and embracing data observability principles while adhering to best practices. Tackling the challenges of reading diverse data sources and formats, you’ll gain a comprehensive understanding of all these.

Our journey continues with essential insights into error logging, identification, resolution, data orchestration, and effective monitoring. You’ll discover optimal approaches for storing logs, ensuring easy access and references for them in the future.

By the end of this book, you’ll possess a fully automated setup to initiate data ingestion and pipeline monitoring. This streamlined process will seamlessly integrate into the subsequent stages of the Extract, Transform, and Load (ETL) process, propelling your data integration capabilities to new heights. Get ready to embark on an enlightening and transformative data ingestion journey.

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