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Data Ingestion with Python Cookbook

You're reading from Data Ingestion with Python Cookbook A practical guide to ingesting, monitoring, and identifying errors in the data ingestion process

Product type Paperback

Published in May 2023

Publisher Packt

ISBN-13 9781837632602

Length 414 pages

Edition 1st Edition

Languages

Python

Tools

Apache Airflow

Concepts

Data Engineering

Author (1):

Gláucia Esppenchutz

View More author details

Table of Contents (17) Chapters

Preface

1. Part 1: Fundamentals of Data Ingestion

2. Chapter 1: Introduction to Data Ingestion FREE CHAPTER

3. Chapter 2: Principals of Data Access – Accessing Your Data

4. Chapter 3: Data Discovery – Understanding Our Data before Ingesting It

5. Chapter 4: Reading CSV and JSON Files and Solving Problems

6. Chapter 5: Ingesting Data from Structured and Unstructured Databases

7. Chapter 6: Using PySpark with Deﬁned and Non-Deﬁned Schemas

8. Chapter 7: Ingesting Analytical Data

9. Part 2: Structuring the Ingestion Pipeline

10. Chapter 8: Designing Monitored Data Workﬂows

11. Chapter 9: Putting Everything Together with Airﬂow

12. Chapter 10: Logging and Monitoring Your Data Ingest in Airﬂow

13. Chapter 11: Automating Your Data Ingestion Pipelines

14. Chapter 12: Using Data Observability for Debugging, Error Handling, and Preventing Downtime

15. Index

Why subscribe?

16. Other Books You May Enjoy

Part 1: Fundamentals of Data Ingestion

In this part, you will be introduced to the fundamentals of data ingestion and data engineering, passing through the basic definition of an ingestion pipeline, the common types of data sources, and the technologies involved.

This part has the following chapters:

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

The rest of the chapter is locked

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Authors (1)

Gláucia Esppenchutz

Gláucia Esppenchutz

Gláucia Esppenchutz is a data engineer with expertise in managing data pipelines and vast amounts of data using cloud and on-premises technologies. She worked in companies such as Globo, BMW Group, and Cloudera. Currently, she works at AiFi, specializing in the field of data operations for autonomous systems. She comes from the biomedical field and shifted her career ten years ago to chase the dream of working closely with technology and data. She is in constant contact with the open source community, mentoring people and helping to manage projects, and has collaborated with the Apache, PyLadies group, FreeCodeCamp, Udacity, and MentorColor communities.

See other products by Gláucia Esppenchutz

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