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Data Engineering with AWS Cookbook. A recipe-based approach to helping you tackle data engineering problems with AWS services

Język publikacji: angielskim
Data Engineering with AWS Cookbook. A recipe-based approach to helping you tackle data engineering problems with AWS services Tram Pham, Gonzalo Herreros González, Vaquar Khan, Huda Nofal - okladka książki

Data Engineering with AWS Cookbook. A recipe-based approach to helping you tackle data engineering problems with AWS services Tram Pham, Gonzalo Herreros González, Vaquar Khan, Huda Nofal - okladka książki

Serie wydawnicze:
Cookbook
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
399
Performing data engineering with Amazon Web Services combines AWS's scalable infrastructure with robust data processing tools, enabling efficient data pipelines and analytics workflows. This comprehensive guide to AWS data engineering will teach you all you need to know about data lake management, pipeline orchestration, and serving layer construction.
Through clear explanations and hands-on exercises, you’ll master essential AWS services like Glue, EMR, Redshift, Athena, and QuickSight. Additionally, you’ll explore data governance, DevOps, CI/CD, and Infrastructure as Code. As you progress, you’ll also gain insights into Tableau Server and Cloud.
By the end of this book, you’ll be well-versed in AWS data engineering and have gained proficiency in key AWS services, mastered data processing techniques, and developed the skills necessary to tackle large-scale data challenges with confidence.

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O autorach książki

Trâm Phấm is a Senior Data and Analytics Consultant with 12 years of experience in the data and analytics field. As a professional services consultant, she helps large-scale enterprises in Vietnam build and launch their data platforms. Having a background in data analytics, business intelligence (BI), and project management, and three years of experience as a big data engineer utilizing Spark and Cloud technologies has allowed her to bring a unique skill set to her role as an AWS Data and Analytics Consultant.
Vaquar Khan is an accomplished Technology Architect and Cloud Architect with over 19 years of IT experience, specializing in large-scale distributed systems, cloud, and Big Data architecture for competitive clients in the BFSI domain. A polyglot developer skilled in Java, Python, and Scala, he excels in designing and implementing innovative solutions, leading by example. Vaquar has extensive hands-on experience in developing distributed systems, multi-tenant cloud-based solutions, and microservices. He is a certified AWS expert with solid experience in GCP, Azure, and Pivotal Cloud Foundry. His expertise includes full-stack development, CI/CD, Docker, Kubernetes, and development process automation. Vaquar has contributed to open-source projects such as Apache Spark and JSR 368, and has proven experience with technologies such as Hadoop, Hive, and Kafka, as well as cloud platforms like AWS EMR, EC2, S3, Cognito, Lambda, Docker, and Kubernetes. His innovative approach ensures business continuity, information security, and data engineering excellence. You can explore more about his work on his GitHub, Stack Overflow, and his blog.
Huda Nofal is a Data Engineer with a strong background in the internet industry. She is skilled in Data Warehousing, Python programming, and Extract, Transform, Load (ETL) processes. Huda also has a keen interest in Deep Learning and Machine Learning. She holds a Bachelor's degree in Computer and Information Systems from the University of Jordan.

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