Book Image

Data Ingestion with Python Cookbook

By : Gláucia Esppenchutz
Book Image

Data Ingestion with Python Cookbook

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)
1
Part 1: Fundamentals of Data Ingestion
9
Part 2: Structuring the Ingestion Pipeline

Scheduling data replication

In the first chapter of this book, we covered what data replication is and why it’s important. We saw how vital this process is in the prevention of data loss and in promoting recovery from disasters.

Now, it is time to learn how to create an optimized schedule window to make data replication happen. In this recipe, we will create a diagram to help us decide the best moment to replicate our data.

Getting ready

This exercise does not require technical preparation. However, to make it closer to a real scenario, let’s imagine we need to decide the best way to ensure the data from a hospital is being adequately replicated.

We will have two pipelines: one holding patient information and another with financial information. The first pipeline collects information from a patient database and synthesizes it into readable reports used by the medical team. The second will feed an internal dashboard used by the hospital executives.

Due to...