{ "item_title" : "End-to-End Data Engineering Projects", "item_author" : [" Greg S. Funchess "], "item_description" : "End-to-End Data Engineering ProjectsEvery day, organizations generate massive volumes of data-from customer interactions and transactions to real-time events and machine learning signals. But raw data has little value without the infrastructure to collect, organize, process, and turn it into actionable insights. That's where data engineering comes in.For aspiring data professionals and developers, entering the field can feel overwhelming. You may know Python or SQL, watched tutorials, or read documentation-but still wonder: How do you build a complete data pipeline from start to finish?How do companies process data at scale?How do tools like Spark, Airflow, Kafka, and cloud platforms work together in production?End-to-End Data Engineering Projects answers these questions through a practical, project-based approach. It guides you through the entire lifecycle of modern data engineering-from raw data ingestion to analytics-ready systems-using realistic architectures and real-world scenarios.What You Will LearnFoundations of modern data engineering and the complete data lifecycleDesigning scalable data pipelines and ETL/ELT workflowsWorking with Python, SQL, Apache Spark, Airflow, and cloud platformsBuilding and managing data lakes, data warehouses, and lakehouse architecturesImplementing batch and real-time streaming pipelines for analyticsIntegrating pipelines with BI tools and analytics platformsApplying data governance, security, and compliance practicesOrchestrating, monitoring, optimizing, and scaling modern pipelinesReal-World Case StudiesE-commerce order analytics pipelinesReal-time event streaming architecturesCloud-based data warehousing solutionsData lake implementation strategiesMachine learning pipeline integrationWho This Book Is ForAspiring data engineers building project-based skillsSoftware engineers transitioning into data infrastructure rolesData analysts and data scientists exploring pipeline architectureEngineers updating knowledge with cloud and streaming technologiesBasic familiarity with Python or SQL is helpful, but no prior experience with large-scale data systems is required.Why This Book MattersData engineering is at the heart of modern technology. Without reliable pipelines, organizations risk incomplete, inconsistent, or inaccessible data-leading to poor decisions. Learning to design scalable data systems is one of today's most valuable technical skills. This book bridges the gap between theory and real-world practice, showing you how to build systems that actually work.Start your journey into data engineering and learn to turn raw data into real business impact.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/825/119/9798251198423_b.jpg", "price_data" : { "retail_price" : "47.99", "online_price" : "47.99", "our_price" : "47.99", "club_price" : "47.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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