Overview
Build Data Systems That Scale-From ETL to Real-Time StreamingThe modern world runs on data. But collecting it is only the beginning. Data Engineering in Practice is your hands-on guide to designing and building reliable, scalable data pipelines-from batch ETL to real-time stream processing.This book is perfect for aspiring data engineers, software developers, and analytics professionals who want to go beyond theory and start building production-grade data infrastructure.You'll learn how to choose the right tools, architect efficient pipelines, and ensure your data flows cleanly from source to storage to insight-all with performance and reliability in mind.Inside You'll Learn: The role of the data engineer in modern analytics and AI stacksHow to build robust ETL and ELT pipelinesReal-time stream processing with tools like Apache Kafka and Spark StreamingOrchestrating workflows using Apache AirflowWorking with structured and unstructured data at scaleData lake vs. data warehouse: when to use whatScaling pipelines with cloud-native tools (AWS, GCP, Azure)Ensuring data quality, observability, and monitoringBest practices for automation, versioning, and reproducibilityWhether you're building your first pipeline or scaling a streaming platform to millions of events per minute, this book will help you do it right-from Day 1.Power your data. Architect the flow. Engineer for scale.
- | Author: Booker Blunt
- | Publisher: Independently Published
- | Publication Date: Jun 29, 2025
- | Number of Pages: 00246 pages
- | Binding: Paperback or Softback
- | ISBN-10: NA
- | ISBN-13: 9798290199948
