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

What not to do – anti-patterns for a data warehouse

While there are many good ways to use a data warehouse for analytics, there are some approaches that at first may seem to be a good fit for a data warehouse but are generally not recommended.

Let’s take a look at some of the ways of using a data warehouse that should be avoided.

Using a data warehouse as a transactional datastore

Data warehouses are designed to be optimized for Online Analytical Processing (OLAP) queries, so they should not be used for Online Transaction Processing (OLTP) queries and use cases.

While there are mechanisms to update or delete data from a data warehouse (such as the merge statement in Redshift), a data warehouse is primarily designed for mostly append-only, or insert, queries. There are also other features of transactional databases (such as MySQL or PostgreSQL) that are available in Redshift – such as the concept of primary and foreign keys – but these are...

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

What not to do – anti-patterns for a data warehouse

Using a data warehouse as a transactional datastore

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