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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

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How to Build a Performant Data Warehouse in Redshift

Sisense

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing).

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Master Your Power BI Environment with Tabular Models

Jet Global

This leads to the second option, which is a data warehouse. In this scenario, data are periodically queried from the source transactional system. It updates a dedicated database against which you can perform reporting and analytics. Within the data warehouse paradigm, there are two divergent approaches.