Dieses Angebot wurde verkauft am Di, 26. Aug um 10:57.
Data Engineering with Python by Paul Crickard (2020, Trade Paperback)
Verkauft
Data Engineering with Python by Paul Crickard (2020, Trade Paperback)
US $14,00US $14,00
Di, 26. Aug, 22:57Di, 26. Aug, 22:57
Solch einen Artikel verkaufen
Mehr Artikel des Verkäufers

Data Engineering with Python by Paul Crickard (2020, Trade Paperback)

cart3rhugh3s
(71)
Angemeldet als privater Verkäufer
Verbraucherschützende Vorschriften, die sich aus dem EU-Verbraucherrecht ergeben, finden daher keine Anwendung. Der eBay-Käuferschutz gilt dennoch für die meisten Käufe.
Mehr Artikel des Verkäufers
Verkäufer kontaktieren
US $14,00
Ca.CHF 11,14
oder Preisvorschlag
Artikelzustand:
Neuwertig
Solch einen Artikel verkaufen
Mehr Artikel des Verkäufers
    Versand:
    US $5,97 (ca. CHF 4,75) USPS Media MailTM.
    Standort: Harpers Ferry, West Virginia, USA
    Lieferung:
    Lieferung zwischen Fr, 31. Okt und Do, 6. Nov nach 94104 bei heutigem Zahlungseingang
    Wir wenden ein spezielles Verfahren zur Einschätzung des Liefertermins an – in diese Schätzung fließen Faktoren wie die Entfernung des Käufers zum Artikelstandort, der gewählte Versandservice, die bisher versandten Artikel des Verkäufers und weitere ein. Insbesondere während saisonaler Spitzenzeiten können die Lieferzeiten abweichen.
    Rücknahme:
    Keine Rücknahme.
    Zahlungen:
         Diners Club

    Sicher einkaufen

    eBay-Käuferschutz
    Geld zurück, wenn etwas mit diesem Artikel nicht stimmt. Mehr erfahreneBay-Käuferschutz - wird in neuem Fenster oder Tab geöffnet
    Der Verkäufer ist für dieses Angebot verantwortlich.
    eBay-Artikelnr.:267369739165

    Artikelmerkmale

    Artikelzustand
    Neuwertig: Buch, das wie neu aussieht, aber bereits gelesen wurde. Der Einband weist keine ...
    ISBN
    9781839214189
    Kategorie

    Über dieses Produkt

    Product Identifiers

    Publisher
    Packt Publishing, The Limited
    ISBN-10
    183921418X
    ISBN-13
    9781839214189
    eBay Product ID (ePID)
    3050401243

    Product Key Features

    Number of Pages
    356 Pages
    Publication Name
    Data Engineering with Python : Work with Massive Datasets to Design Data Models and Automate Data Pipelines Using Python
    Language
    English
    Subject
    Data Modeling & Design, Databases / Data Warehousing, Data Processing
    Publication Year
    2020
    Type
    Textbook
    Subject Area
    Computers
    Author
    Paul Crickard
    Format
    Trade Paperback

    Dimensions

    Item Length
    3.6 in
    Item Width
    3 in

    Additional Product Features

    Intended Audience
    Trade
    Table Of Content
    Table of Contents What is Data Engineering? Building Our Data Engineering Infrastructure Reading and Writing Files Working with Databases Cleaning, Transforming, and Enriching Data Building a 311 Data Pipeline Features of a Production Pipeline Version Control Using the NiFi Registry Monitoring and Logging Pipelines Deploying your Pipelines Building a Production Data Pipeline Building a Kafka Cluster Streaming Data with Apache Kafka Data Processing with Apache Spark Real-Time Edge Data with MiNiFi, Kafka, and Spark Appendix
    Synopsis
    Build, monitor, and manage real-time data pipelines to create data engineering infrastructure efficiently using open-source Apache projects Key Features Become well-versed in data architectures, data preparation, and data optimization skills with the help of practical examples Design data models and learn how to extract, transform, and load (ETL) data using Python Schedule, automate, and monitor complex data pipelines in production Book Description Data engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You'll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You'll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you'll build architectures on which you'll learn how to deploy data pipelines. By the end of this Python book, you'll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production. What you will learn Understand how data engineering supports data science workflows Discover how to extract data from files and databases and then clean, transform, and enrich it Configure processors for handling different file formats as well as both relational and NoSQL databases Find out how to implement a data pipeline and dashboard to visualize results Use staging and validation to check data before landing in the warehouse Build real-time pipelines with staging areas that perform validation and handle failures Get to grips with deploying pipelines in the production environment Who this book is for This book is for data analysts, ETL developers, and anyone looking to get started with or transition to the field of data engineering or refresh their knowledge of data engineering using Python. This book will also be useful for students planning to build a career in data engineering or IT professionals preparing for a transition. No previous knowledge of data engineering is required., Build, monitor, and manage real-time data pipelines to create data engineering infrastructure efficiently using open-source Apache projects Key features: Become well-versed in data architectures, data preparation, and data optimization skills with the help of practical examples Design data models and learn how to extract, transform, and load (ETL) data using Python Schedule, automate, and monitor complex data pipelines in production Book Description Data engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You'll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You'll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you'll build architectures on which you'll learn how to deploy data pipelines. By the end of this Python book, you'll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production. What you will learn Understand how data engineering supports data science workflows Discover how to extract data from files and databases and then clean, transform, and enrich it Configure processors for handling different file formats as well as both relational and NoSQL databases Find out how to implement a data pipeline and dashboard to visualize results Use staging and validation to check data before landing in the warehouse Build real-time pipelines with staging areas that perform validation and handle failures Get to grips with deploying pipelines in the production environment Who this book is for This book is for data analysts, ETL developers, and anyone looking to get started with or transition to the field of data engineering or refresh their knowledge of data engineering using Python. This book will also be useful for students planning to build a career in data engineering or IT professionals preparing for a transition. No previous knowledge of data engineering is required., This book is a comprehensive introduction to building data pipelines, that will have you moving and transforming data in no time. You'll learn how to build data pipelines, transform and clean data, and deliver it to provide value to users. You will learn to deploy production data pipelines that include logging, monitoring, and version control.

    Artikelbeschreibung des Verkäufers

    Info zu diesem Verkäufer

    cart3rhugh3s

    100% positive Bewertungen•83 Artikel verkauft

    Mitglied seit Aug 2015
    Antwortet meist innerhalb 24 Stunden
    Angemeldet als privater VerkäuferDaher finden verbraucherschützende Vorschriften, die sich aus dem EU-Verbraucherrecht ergeben, keine Anwendung. Der eBay-Käuferschutz gilt dennoch für die meisten Käufe.
    Mehr Artikel des VerkäufersKontakt

    Detaillierte Verkäuferbewertungen

    Durchschnitt in den letzten 12 Monaten
    Genaue Beschreibung
    4.9
    Angemessene Versandkosten
    4.6
    Lieferzeit
    5.0
    Kommunikation
    5.0

    Verkäuferbewertungen (46)

    Alle Bewertungenselected
    Positiv
    Neutral
    Negativ
    Alle Bewertungen ansehen

    Noch mehr entdecken: