You're reading from Data Engineering with AWS - Second Edition

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Published inOct 2023

PublisherPackt

ISBN-139781804614426

Edition2nd Edition

Concepts

Data Engineering

Author (1)

Gareth Eagar

Loading data into data marts

Many tools can work directly with data in the data lake, as we covered in Chapter 3, The AWS Data Engineer’s Toolkit. These include tools for ad hoc SQL queries (Amazon Athena), data processing tools (such as Amazon EMR and AWS Glue), and even specialized machine learning tools (such as Amazon SageMaker).

These tools read data directly from Amazon S3, but there are times when a use case may require much lower latency and higher performance reads of the data. Alternatively, there may be times when the use of highly structured schemas may best meet the analytic requirements of the use case. In these cases, loading data from the data lake into a data mart makes sense.

In analytic environments, a data mart is most often a data warehouse system (such as Amazon Redshift or Snowflake), but it could also be a relational database system (such as Amazon RDS for MySQL), depending on the use case’s requirements. In either case, the system will...

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Data Engineering with AWS - Second Edition

Published in: Oct 2023Publisher: PacktISBN-13: 9781804614426

Author (1)

Gareth Eagar

Gareth Eagar has over 25 years of experience in the IT industry, starting in South Africa, working in the United Kingdom for a while, and now based in the USA. Having worked at AWS since 2017, Gareth has broad experience with a variety of AWS services, and deep expertise around building data platforms on AWS. While Gareth currently works as a Solutions Architect, he has also worked in AWS Professional Services, helping architect and implement data platforms for global customers. Gareth frequently speaks on data related topics.
Read more about Gareth Eagar

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Loading data into data marts

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