Data Ingestion with Python Cookbook: A practical guide to ingesting, monitoring,

AlibrisBooks
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Item specifics

Condition
New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Data Ingestion with Python Cookbook: A practical guide to ingesti
Publication Date
2023-05-31
Pages
414
ISBN
9781837632602
Category

About this product

Product Identifiers

Publisher
Packt Publishing, The Limited
ISBN-10
183763260X
ISBN-13
9781837632602
eBay Product ID (ePID)
14061936576

Product Key Features

Number of Pages
368 Pages
Publication Name
Data Ingestion with Python Cookbook : A Practical Guide Helping You Ingest, Monitor, and Identify Errors in the Data Ingestion Process
Language
English
Publication Year
2023
Subject
General, Data Processing
Type
Textbook
Subject Area
Mathematics, Computers
Author
Gláucia Esppenchutz
Format
Trade Paperback

Dimensions

Item Length
92.5 in
Item Width
75 in

Additional Product Features

Intended Audience
Trade
Dewey Edition
23
Dewey Decimal
005.74
Synopsis
Deploy your data ingestion pipeline, orchestrate, and monitor efficiently to prevent loss of data and quality Purchase of the print or Kindle book includes a free PDF eBook Key Features: Harness best practices to create a Python and PySpark data ingestion pipeline Seamlessly automate and orchestrate your data pipelines using Apache Airflow Build a monitoring framework by integrating the concept of data observability into your pipelines Book Description: 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. What You Will Learn: Implement data observability using monitoring tools Automate your data ingestion pipeline Read analytical and partitioned data, whether schema or non-schema based Debug and prevent data loss through efficient data monitoring and logging Establish data access policies using a data governance framework Construct a data orchestration framework to improve data quality Who this book is for: This book is for data engineers and data enthusiasts seeking a comprehensive understanding of the data ingestion process using popular tools in the open source community. For more advanced learners, this book takes on the theoretical pillars of data governance while providing practical examples of real-world scenarios commonly encountered by data engineers., Deploy your data ingestion pipeline, orchestrate, and monitor efficiently to prevent loss of data and quality Key Features Harness best practices to create a Python and PySpark data ingestion pipeline Seamlessly automate and orchestrate your data pipelines using Apache Airflow Build a monitoring framework by integrating the concept of data observability into your pipelines Book Description 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. What you will learn Implement data observability using monitoring tools Automate your data ingestion pipeline Read analytical and partitioned data, whether schema or non-schema based Debug and prevent data loss through efficient data monitoring and logging Establish data access policies using a data governance framework Construct a data orchestration framework to improve data quality Who this book is for This book is for data engineers and data enthusiasts seeking a comprehensive understanding of the data ingestion process using popular tools in the open source community. For more advanced learners, this book takes on the theoretical pillars of data governance while providing practical examples of real-world scenarios commonly encountered by data engineers. ]]>
LC Classification Number
QA76.9.D343

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