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Data Ingestion with Python Cookbook

You're reading from  Data Ingestion with Python Cookbook

Product type Book
Published in May 2023
Publisher Packt
ISBN-13 9781837632602
Pages 414 pages
Edition 1st Edition
Languages
Author (1):
Gláucia Esppenchutz Gláucia Esppenchutz
Profile icon Gláucia Esppenchutz

Table of Contents (17) Chapters

Preface Part 1: Fundamentals of Data Ingestion
Chapter 1: Introduction to Data Ingestion Chapter 2: Principals of Data Access – Accessing Your Data Chapter 3: Data Discovery – Understanding Our Data before Ingesting It Chapter 4: Reading CSV and JSON Files and Solving Problems Chapter 5: Ingesting Data from Structured and Unstructured Databases Chapter 6: Using PySpark with Defined and Non-Defined Schemas Chapter 7: Ingesting Analytical Data Part 2: Structuring the Ingestion Pipeline
Chapter 8: Designing Monitored Data Workflows Chapter 9: Putting Everything Together with Airflow Chapter 10: Logging and Monitoring Your Data Ingest in Airflow Chapter 11: Automating Your Data Ingestion Pipelines Chapter 12: Using Data Observability for Debugging, Error Handling, and Preventing Downtime Index Other Books You May Enjoy

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...

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