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Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features

(ebook) (audiobook) (audiobook) Książka w języku 1
Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features Vishal Pathak, Subramanya Vajiraya, Noritaka Sekiyama, Tomohiro Tanaka, Albert Quiroga, Ishan Gaur - okladka książki

Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features Vishal Pathak, Subramanya Vajiraya, Noritaka Sekiyama, Tomohiro Tanaka, Albert Quiroga, Ishan Gaur - okladka książki

Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features Vishal Pathak, Subramanya Vajiraya, Noritaka Sekiyama, Tomohiro Tanaka, Albert Quiroga, Ishan Gaur - audiobook MP3

Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features Vishal Pathak, Subramanya Vajiraya, Noritaka Sekiyama, Tomohiro Tanaka, Albert Quiroga, Ishan Gaur - audiobook CD

Serie wydawnicze:
Learning
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
434
Dostępne formaty:
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     ePub

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Do przechowalni

Organizations these days have gravitated toward services such as AWS Glue that undertake undifferentiated heavy lifting and provide serverless Spark, enabling you to create and manage data lakes in a serverless fashion. This guide shows you how AWS Glue can be used to solve real-world problems along with helping you learn about data processing, data integration, and building data lakes.
Beginning with AWS Glue basics, this book teaches you how to perform various aspects of data analysis such as ad hoc queries, data visualization, and real-time analysis using this service. It also provides a walk-through of CI/CD for AWS Glue and how to shift left on quality using automated regression tests. You’ll find out how data security aspects such as access control, encryption, auditing, and networking are implemented, as well as getting to grips with useful techniques such as picking the right file format, compression, partitioning, and bucketing. As you advance, you’ll discover AWS Glue features such as crawlers, Lake Formation, governed tables, lineage, DataBrew, Glue Studio, and custom connectors. The concluding chapters help you to understand various performance tuning, troubleshooting, and monitoring options.
By the end of this AWS book, you’ll be able to create, manage, troubleshoot, and deploy ETL pipelines using AWS Glue.

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O autorach książki

Vishal Pathak is a Data Lab Solutions Architect at AWS. Vishal works with customers on their use cases, architects solutions to solve their business problems, and helps them build scalable prototypes. Prior to his journey in AWS, Vishal helped customers implement business intelligence, data warehouse, and data lake projects in the US and Australia.
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.
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
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.
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.
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.

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