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Serverless ETL and Analytics with AWS Glue. Design scalable data lakes, optimize ETL pipelines, and accelerate analytics on AWS - Second Edition Noritaka Sekiyama, Albert Quiroga, Tomohiro Tanaka, Subramanya Vajiraya, Akira Ajisaka, Ishan Gaur

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Serverless ETL and Analytics with AWS Glue. Design scalable data lakes, optimize ETL pipelines, and accelerate analytics on AWS - Second Edition Noritaka Sekiyama, Albert Quiroga, Tomohiro Tanaka, Subramanya Vajiraya, Akira Ajisaka, Ishan Gaur - okladka książki

Serverless ETL and Analytics with AWS Glue. Design scalable data lakes, optimize ETL pipelines, and accelerate analytics on AWS - Second Edition Noritaka Sekiyama, Albert Quiroga, Tomohiro Tanaka, Subramanya Vajiraya, Akira Ajisaka, Ishan Gaur - okladka książki

Serverless ETL and Analytics with AWS Glue. Design scalable data lakes, optimize ETL pipelines, and accelerate analytics on AWS - Second Edition Noritaka Sekiyama, Albert Quiroga, Tomohiro Tanaka, Subramanya Vajiraya, Akira Ajisaka, Ishan Gaur - audiobook MP3

Serverless ETL and Analytics with AWS Glue. Design scalable data lakes, optimize ETL pipelines, and accelerate analytics on AWS - Second Edition Noritaka Sekiyama, Albert Quiroga, Tomohiro Tanaka, Subramanya Vajiraya, Akira Ajisaka, Ishan Gaur - audiobook CD

Autorzy:
Noritaka Sekiyama, Albert Quiroga, Tomohiro Tanaka, Subramanya Vajiraya, Akira Ajisaka, Ishan Gaur
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Building a modern data platform is no longer just about moving data. Organizations must scale reliably, control costs, enforce governance, and accelerate analytics. This book shows you how to design and operate production-grade data platforms using AWS Glue and related AWS analytics services.
You will begin with core data management concepts before moving into ingestion from diverse sources, data preparation strategies, metadata management, security controls, and cross-account data sharing. Learn how to design efficient data layouts, orchestrate pipelines, implement CI CD practices, and manage the full lifecycle of data integration workloads.
This updated edition expands coverage of open table formats such as Apache Hudi, Delta Lake, and Apache Iceberg, along with performance tuning, observability, cost optimization, and real-world troubleshooting. You will also explore integrations with machine learning and generative AI workflows powered by Glue and SageMaker.
Written by AWS engineers and architects with deep hands-on experience in large-scale enterprise data lakes, this guide blends architecture principles with real-world implementation insight.
By the end of this book, you will be able to design, deploy, monitor, and optimize scalable serverless ETL pipelines and governed data platforms on AWS.

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O autorach książki

Noritaka Sekiyama is a Senior Big Data Architect on the AWS Glue and AWS Lake Formation team. He has 11 years of experience working in the software industry. Based in Tokyo, Japan, he is responsible for implementing software artifacts, building libraries, troubleshooting complex issues and helping guide customer architectures
Albert Quiroga works as a senior solutions architect at Amazon, where he is helping to design and architect one of the largest data lakes in the world. Prior to that, he spent four years working at AWS, where he specialized in big data technologies such as EMR and Athena, and where he became an expert on AWS Glue. Albert has worked with several Fortune 500 companies on some of the largest data lakes in the world and has helped to launch and develop features for several AWS services.
Tomohiro Tanaka is a senior cloud support engineer at AWS. He works to help customers solve their issues and build data lakes across AWS Glue, AWS IoT, and big data technologies such Apache Spark, Hadoop, and Iceberg.
Subramanya Vajiraya is a Big data Cloud Engineer at AWS Sydney specializing in AWS Glue. He obtained his Bachelor of Engineering degree specializing in Information Science & Engineering from NMAM Institute of Technology, Nitte, KA, India (Visvesvaraya Technological University, Belgaum) in 2015 and obtained his Master of Information Technology degree specialized in Internetworking from the University of New South Wales, Sydney, Australia in 2017. He is passionate about helping customers solve challenging technical issues related to their ETL workload and implementing scalable data integration and analytics pipelines on AWS.
Akira Ajisaka is a software engineer and has more than 10 years of engineering experience in big data. He likes troubleshooting and contributing to OSS.
Ishan Gaur has more than 13 years of IT experience in soft ware development and data engineering, building distributed systems and highly scalable ETL pipelines using Apache Spark, Scala, and various ETL tools such as Ab Initio and Datastage. He currently works at AWS as a senior big data cloud engineer and is an SME of AWS Glue. He is responsible for helping customers to build out large, scalable distributed systems and implement them in AWS cloud environments using various big data services, including EMR, Glue, and Athena, as well as other technologies, such as Apache Spark, Hadoop, and Hive.

Packt Publishing - inne książki

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