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Summary

In today’s data-driven world, organizations generate and process massive volumes of information every second. Big Data Engineering provides a practical introduction to the technologies, architectures, and engineering principles that power modern data platforms. 
Designed for students, aspiring data engineers, software developers, IT professionals, and technology enthusiasts, this book explores the complete lifecycle of big data—from data ingestion and storage to processing, analytics, governance, and scalability. Readers will learn how to design reliable data pipelines, build distributed systems, and manage large-scale data environments that support business intelligence, machine learning, and real-time decision-making. 
Inside this book, you will discover:Core concepts of big data and distributed computingData lakes, data warehouses, and modern data architecturesBatch processing and real-time streaming systemsETL and ELT pipeline design and implementationCloud-based data engineering platforms and servicesData modeling, storage optimization, and performance tuningData quality, governance, security, and complianceScalability, fault tolerance, and high-availability strategiesEmerging trends in analytics, artificial intelligence, and data ecosystems 
Written in a clear and accessible style, Big Data Engineering combines foundational theory with practical insights to help readers understand how modern organizations transform raw data into valuable business assets.

Duration: about 3 hours (03:03:00)
Publishing date: 2026-06-21; Unabridged; Copyright Year: — Copyright Statment: —

• Science & Technology