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{ "item_title" : "Data Engineering Essentials", "item_author" : [" Vedant Pandya "], "item_description" : "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 engineeringPython for data pipelines and automationData modelling and warehouse designETL and ELT architectureApache Airflow orchestrationApache Kafka streaming systemsData quality and governanceSnowflake, BigQuery, and RedshiftData lakes and lakehouse architectureApache Spark processing at scaledbt transformation frameworksDataOps and pipeline automationCloud-native data platformsReal-time analytics and streaming architecturesMLOps and AI data infrastructureBuilding scalable modern data ecosystemsUnlike 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.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/818/242/9798182420303_b.jpg", "price_data" : { "retail_price" : "12.99", "online_price" : "12.99", "our_price" : "12.99", "club_price" : "12.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Data Engineering Essentials|Vedant Pandya

Data Engineering Essentials : The Complete Guide to Building Data Pipelines, Data Warehouses, and Modern Data Platforms - From SQL and Python to Spark,

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Overview

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.

This item is Non-Returnable

Details

  • ISBN-13: 9798182420303
  • ISBN-10: 9798182420303
  • Publisher: Independently Published
  • Publish Date: June 2026
  • Dimensions: 9 x 6 x 0.39 inches
  • Shipping Weight: 0.56 pounds
  • Page Count: 184

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