Unlock the Power of Modern Data Engineering with Python. Transform raw data into actionable insights and scalable systems with practical, hands-on guidance.
Dive into the world of modern data engineering as this book takes you step by step through building reliable ETL pipelines, automating workflows, and handling big data efficiently using Python. From foundational concepts to advanced techniques, you’ll learn how to clean, transform, and validate data, orchestrate workflows, implement fault-tolerant pipelines, and scale processing for enterprise-grade systems. Real-world examples, mini-projects, and detailed Python implementations make complex concepts easy to understand and apply.
Whether you’re a developer, data analyst, or aspiring data engineer, this book equips you with the skills to build end-to-end data systems. Learn how to optimize performance, maintain data quality, and implement observability to ensure your data pipelines are trustworthy and production-ready. By combining theoretical principles with practical, hands-on exercises, you’ll gain confidence in designing, deploying, and maintaining robust data engineering solutions.
What readers will gain from this book:
Mastery of ETL and ELT pipeline design for modern data systems.
Practical Python skills for automating data ingestion, transformation, and loading.
Techniques to ensure pipeline reliability, fault tolerance, and observability.
Strategies for handling big data and scalable distributed processing.
Best practices for testing, monitoring, and productionizing data pipelines.
Start building modern, reliable, and scalable data engineering systems today, take control of your data and transform it into business value with Python.
"Sinopsis" puede pertenecer a otra edición de este libro.
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Print on Demand. Nº de ref. del artículo: I-9798279121038
Cantidad disponible: Más de 20 disponibles
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Paperback. Condición: new. Paperback. Unlock the Power of Modern Data Engineering with Python. Transform raw data into actionable insights and scalable systems with practical, hands-on guidance.Dive into the world of modern data engineering as this book takes you step by step through building reliable ETL pipelines, automating workflows, and handling big data efficiently using Python. From foundational concepts to advanced techniques, you'll learn how to clean, transform, and validate data, orchestrate workflows, implement fault-tolerant pipelines, and scale processing for enterprise-grade systems. Real-world examples, mini-projects, and detailed Python implementations make complex concepts easy to understand and apply.Whether you're a developer, data analyst, or aspiring data engineer, this book equips you with the skills to build end-to-end data systems. Learn how to optimize performance, maintain data quality, and implement observability to ensure your data pipelines are trustworthy and production-ready. By combining theoretical principles with practical, hands-on exercises, you'll gain confidence in designing, deploying, and maintaining robust data engineering solutions.What readers will gain from this book: Mastery of ETL and ELT pipeline design for modern data systems.Practical Python skills for automating data ingestion, transformation, and loading.Techniques to ensure pipeline reliability, fault tolerance, and observability.Strategies for handling big data and scalable distributed processing.Best practices for testing, monitoring, and productionizing data pipelines.Start building modern, reliable, and scalable data engineering systems today, take control of your data and transform it into business value with Python. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798279121038
Cantidad disponible: 1 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798279121038
Cantidad disponible: Más de 20 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. Unlock the Power of Modern Data Engineering with Python. Transform raw data into actionable insights and scalable systems with practical, hands-on guidance.Dive into the world of modern data engineering as this book takes you step by step through building reliable ETL pipelines, automating workflows, and handling big data efficiently using Python. From foundational concepts to advanced techniques, you'll learn how to clean, transform, and validate data, orchestrate workflows, implement fault-tolerant pipelines, and scale processing for enterprise-grade systems. Real-world examples, mini-projects, and detailed Python implementations make complex concepts easy to understand and apply.Whether you're a developer, data analyst, or aspiring data engineer, this book equips you with the skills to build end-to-end data systems. Learn how to optimize performance, maintain data quality, and implement observability to ensure your data pipelines are trustworthy and production-ready. By combining theoretical principles with practical, hands-on exercises, you'll gain confidence in designing, deploying, and maintaining robust data engineering solutions.What readers will gain from this book: Mastery of ETL and ELT pipeline design for modern data systems.Practical Python skills for automating data ingestion, transformation, and loading.Techniques to ensure pipeline reliability, fault tolerance, and observability.Strategies for handling big data and scalable distributed processing.Best practices for testing, monitoring, and productionizing data pipelines.Start building modern, reliable, and scalable data engineering systems today, take control of your data and transform it into business value with Python. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798279121038
Cantidad disponible: 1 disponibles