Data Engineering with Python: Work with massive datasets to design data models and automate data pipelines using Python
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Data Engineering with Python: Work with massive datasets to design data models and automate data pipelines using Python
This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python.
Data Engineering with Python: Work with massive datasets to design data models and automate data pipelines using Python
Προϊόν #: 54659559

Data Engineering with Python: Work with massive datasets to design data models and automate data pipelines using Python

89% of respondents would recommend this to a friend

Προϊόν #: 54659559

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What Stands Out

Massive Datasets
Learn how to manage and manipulate large datasets effectively, ensuring data integrity and optimized performance for real-world applications.
Data Models Design
Gain essential skills in designing robust data models that cater to various business needs, enhancing data accessibility and usability.
Automated Pipelines
Master the automation of data pipelines using Python, streamlining workflows and reducing manual intervention for increased efficiency and reliability.

Λεπτομέρειες προιόντος

Design data models and automate data pipelines using Python. Work with massive datasets. Get the book now! Ubuy KW, a Greece.
  • Build, monitor, and manage real-time data pipelines using Python
  • Gain practical experience in data architectures, data preparation, and data optimization
  • Learn how to design data models and perform ETL (Extract, Transform, Load) using Python
  • Schedule, automate, and monitor complex data pipelines in production
  • Explore various tools and methods used in data engineering
  • Build data engineering pipelines for tracking, quality checks, and production changes
Publisher Packt Publishing
Publication date 23 Oct. 2020
Language English
Print length 356 pages
ISBN-10 183921418X
ISBN-13 978-1839214189
Item weight 612 g
Dimensions 19.05 x 2.06 x 23.5 cm

Who Should Buy?

Suitable For
  • Aspiring Data Engineers

    Ideal for individuals seeking to enter the data engineering field with practical skills and knowledge using Python.

  • Data Analysts

    Helpful for analysts looking to enhance their skills in managing and manipulating large datasets effectively.

  • Python Developers

    Valuable for developers wanting to expand their expertise into data engineering and related technologies.

Not Suitable For
  • Beginners in Programming

    Not suitable for those without basic programming knowledge as it may be overwhelming and complex.

ΠΕΡΙΓΡΑΦΗ ΤΟΥ ΠΡΟΪΟΝΤΟΣ

Data Engineering with Python: Work with massive datasets to design data models and automate data pipelines using Python

About This Item

Take your data engineering skills to the next level with Data Engineering with Python. This comprehensive guide will equip you with the knowledge and techniques necessary to work with massive datasets, design efficient data models, and automate complex data pipelines using the power of Python. With the increasing volume and complexity of data in today's world, data engineers play a crucial role in organizing and transforming raw data into valuable insights. This book will teach you how to leverage the flexibility and scalability of Python to streamline your data engineering workflows and unlock the potential of your data. Whether you are a seasoned data engineer looking to enhance your skills or a beginner eager to dive into the world of data engineering, this book is your ultimate resource.

You will learn how to build robust data models that can handle large volumes of data and adapt to changing requirements. This includes techniques for data cleaning, data transformation, and data integration using Python. Automation is a key aspect of modern data engineering, and this book will guide you through the process of automating data pipelines with Python. You will learn how to schedule and orchestrate data pipelines, ensure data quality and reliability, and monitor and troubleshoot your workflows. In addition, this book covers best practices for Python data engineering, providing guidance on how to optimize performance, ensure scalability, and maintain code quality.

It also introduces a range of useful Python libraries and frameworks specifically designed for data engineering tasks, such as Apache Airflow, Pandas, and SQLAlchemy. To help you apply your newly acquired skills in real-world scenarios, this book includes hands-on projects and tutorials. You will explore various data engineering use cases and tackle practical challenges using Python. Whether you are working with structured or unstructured data, Data Engineering with Python will empower you to tackle complex data engineering tasks with confidence and efficiency. Get started on your data engineering journey today and unlock the full potential of your data with Python.

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Data Warehousing Editorial Review

Data Engineering With Python: Work With Massive Datasets To Design Data Models And Automate Data Pipelines Using Python offers an in-depth exploration of data engineering concepts using Python. The book, published by Packt Publishing on 23 Oct. 2020, spans 356 pages and is designed for practitioners looking to enhance their skills in managing massive datasets. Whether you are a beginner or an experienced developer, the practical guidance in this book can empower you to automate data pipelines effectively. Readers have applauded its comprehensive approach, making complex topics more accessible for all levels.

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Πλεονεκτήματα

  • Comprehensive coverage of data engineering concepts
  • Practical guidance for automating data pipelines
  • Clear examples using Python for real-world applications
  • Well-structured for both beginners and experienced users
  • Detailed insights into designing data models

Μειονεκτήματα

  • Some advanced topics may require additional resources

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Χαρακτηριστικά & Πλεονεκτήματα

  • Learn data architectures and how to prepare and optimize data using Python
  • Understand ETL and building data pipelines to work with large datasets
  • Transform and analyze data to gain insights
  • Build and deploy production-ready data pipelines
  • Ideal for data analysts, ETL developers, and those looking to transition to data engineering or advance their skills
  • No previous knowledge of data engineering required

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