Data Engineering Essentials: The Complete Guide to Building Data Pipelines, Data Warehouses, and Modern Data Platforms - From SQL and Python to Spark, ... Data Stack (The Cloud Engineering Library) - Couverture souple

Livre 2 sur 3: The Cloud Engineering Library

Pandya, Vedant

9798182420303: Data Engineering Essentials: The Complete Guide to Building Data Pipelines, Data Warehouses, and Modern Data Platforms - From SQL and Python to Spark, ... Data Stack (The Cloud Engineering Library)

Couverture souple

ISBN 13 : 9798182420303

Editeur : Independently published, 2026

Afficher les exemplaires de cette �dition comportant l'ISBN

0 D'occasion

2 Neuf

De EUR 16,24

Data is the foundation of modern business.

Every dashboard, recommendation engine, AI model, analytics report, and business decision depends on one thing: reliable data.

But raw data is rarely useful on its own.

The truth is simple:

Organizations need engineers who can collect, move, transform, validate, store, and deliver data at scale.

That is the role of the modern Data Engineer.

In Data Engineering Essentials, Ethan Vale provides a practical guide to designing and building modern data platforms using the tools, architectures, and best practices used by today's leading technology companies.

Written for aspiring data engineers, software developers, analysts, cloud professionals, DevOps engineers, and technology leaders, this book explains the complete modern data stack—from foundational SQL and Python skills to large-scale processing, cloud data warehouses, streaming platforms, and MLOps.

Inside this book, you'll learn:

SQL for modern data engineering
Python for data pipelines and automation
Data modelling and warehouse design
ETL and ELT architecture
Apache Airflow orchestration
Apache Kafka streaming systems
Data quality and governance
Snowflake, BigQuery, and Redshift
Data lakes and lakehouse architecture
Apache Spark processing at scale
dbt transformation frameworks
DataOps and pipeline automation
Cloud-native data platforms
Real-time analytics and streaming architectures
MLOps and AI data infrastructure
Building scalable modern data ecosystems

Unlike highly technical data engineering resources that focus on individual tools in isolation, this guide provides a complete understanding of how modern data platforms are designed, built, operated, and scaled in real-world environments.

Whether you're entering data engineering, transitioning from analytics, expanding your cloud skills, or building production-grade data platforms, this book provides the knowledge and practical foundation needed to succeed in one of the fastest-growing fields in technology.

The future belongs to organizations that can turn data into decisions.

Learn how to build the systems that make it possible.

Scroll up and get your copy today.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.