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

Implementing governance in a data access workflow

As we saw previously, data access or accessibility is a governance pillar and is closely related to security. Data safety is not only a concern for administrators or managers but also for everyone that is involved with data. Having said that, it is essential to know how to design a base workflow to implement security layers for our data, allowing only authorized people to read or manipulate it.

This recipe will create a workflow with essential topics to implement data access management.

Getting ready

Before designing our workflow, we need to identify the vectors interfering with our data access.

So, what are data vectors?

Vectors are paths someone can use to gain unauthorized access to a server, network, or database. In this case, we will identify the ones related to data leaks.

Let’s explore them in a visual form, as shown in the following diagram:

Figure 2.1 – Data governance vectors

Figure 2.1 – Data governance...