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Data Ingestion with Python Cookbook A practical guide to ingesting, monitorin...
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Data Ingestion with Python Cookbook | 616 | Gláucia Esppenchutz | 2023 | Packt Publishing Pvt Ltd | ‎ B0C3CQDYHW

Deploy your own data ingestion pipeline, orchestrate, and monitor efficiently to prevent loss of data and quality.

Key Features
  • Implement the best practices to create a data Ingestion pipeline using python and pySpark
    Automate and orchestrate your data pipelines using Apache Airflow
    Build a monitoring framework while applying the concept of data observability to your pipelines

Book Description
Data Ingestion with Python Cookbook brings a practical way to design and apply data ingestion pipelines, providing real-world examples with the most reputed open-source tools available on the market, and bringing enlightenment to questions or obstacles.
You will be introduced to designing and working with or without data schemas, and creating monitored pipelines with airflow and data observability principles, while following the best practices. The book will further address the challenges to read different data sources or data formats. You will then progress to gain a broad understanding of the best practices for logging errors, how to identify/solve them, data orchestration, monitoring, and where to store the logs for further consultation.
By the end of the book, You will have a complete automated set to start ingesting and monitoring the pipeline, making it easier to plug into the further steps of the ETL process later.
What you will learn
  • Apply data observability using monitoring tools
    Automate your data ingestion pipeline
    Read analytical and partitioned data with schema or non-schema
    Debug and prevent data loss using efficient monitoring and logging
    Apply data access policies using a data governance framework
    Create a data orchestration framework to improve data quality

Who This Book Is For
This book is for Data Engineers and data enthusiasts who want to have a better understanding of the process of ingesting data using the most popular tools in the open-source community.
For more advanced learners, this book takes on the theoretical pillars of Data Governance and gives practical examples of real scenarios frequently seen on a daily basis by data engineers.
Table of Contents
  • GRAPHIC BUNDLE present Introduction to Data Ingestion
    Data Access Principals - Accessing your data
    Data Discovery - Understanding our data before ingesting
    Reading CSV and JSON files and solving problems
    Ingesting Data from Structured and Unstructured DataBases
    Using PySpark with defined and non-defined schemas
    Ingesting Analytical Data
    Designing Monitored Data Workflows
    Putting everything together with Airflow
    Logging and Monitoring your Data Ingest in Airflow
    Automate your Data Pipelines
    Using Data Observability to Debug, Error Handling, and Prevent Downtimes

Files:
Data Ingestion with Python Cookbook A practical guide to ingesting, monitoring.epub (31.04 MB)

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