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You're reading from  Serverless ETL and Analytics with AWS Glue

Product typeBook
Published inAug 2022
Reading LevelExpert
PublisherPackt
ISBN-139781800564985
Edition1st Edition
Languages
Python
Tools
AWS Glue
Concepts
Data Analysis
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Authors (6):
Vishal Pathak
Vishal Pathak
author image
Vishal Pathak

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.
Read more about Vishal Pathak

Subramanya Vajiraya
Subramanya Vajiraya
author image
Subramanya Vajiraya

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.
Read more about Subramanya Vajiraya

Noritaka Sekiyama
Noritaka Sekiyama
author image
Noritaka Sekiyama

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
Read more about Noritaka Sekiyama

Tomohiro Tanaka
Tomohiro Tanaka
author image
Tomohiro Tanaka

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.
Read more about Tomohiro Tanaka

Albert Quiroga
Albert Quiroga
author image
Albert Quiroga

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.
Read more about Albert Quiroga

Ishan Gaur
Ishan Gaur
author image
Ishan Gaur

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.
Read more about Ishan Gaur

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Features of AWS Glue

AWS Glue has different features that appear disjointed, but in reality, they are interdependent. Often, users have to use a combination of these features to achieve their goals.

The following are the key features of AWS Glue:

  • AWS Glue Data Catalog
  • AWS Glue Connections
  • AWS Glue Crawlers and Classifiers
  • AWS Glue Schema Registry
  • AWS Glue Jobs
  • AWS Glue Notebooks and interactive sessions
  • AWS Glue Triggers
  • AWS Glue Workflows
  • AWS Glue Blueprints
  • AWS Glue ML
  • AWS Glue Studio
  • AWS Glue DataBrew
  • AWS Glue Elastic Views

Now that we know the different features and services involved in executing an AWS Glue workload, let’s discuss the fundamental concepts related to some of these features.

AWS Glue Data Catalog

A Data Catalog can be defined as an inventory of data assets in an organization that helps data professionals find and understand relevant datasets to extract business value. A Data Catalog...

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Serverless ETL and Analytics with AWS Glue
Published in: Aug 2022Publisher: PacktISBN-13: 9781800564985
© 2022 Packt Publishing Limited All Rights Reserved

Authors (6)

author image
Vishal Pathak

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.
Read more about Vishal Pathak

author image
Subramanya Vajiraya

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.
Read more about Subramanya Vajiraya

author image
Noritaka Sekiyama

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
Read more about Noritaka Sekiyama

author image
Tomohiro Tanaka

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.
Read more about Tomohiro Tanaka

author image
Albert Quiroga

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.
Read more about Albert Quiroga

author image
Ishan Gaur

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.
Read more about Ishan Gaur

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