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Data Modeling 201 for the cloud: designing databases for data warehouses

erwin

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. In fact, many commonly accepted best practices for designing OLTP databases could well be considered worst practices for these purely analytical systems. Look at Figure 1 below.

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The Data Warehouse is Dead, Long Live the Data Warehouse, Part II

Data Virtualization

Reading Time: 4 minutes My previous post explained that, in my mind, the data lakehouse differs hardly at all from the traditional data warehouse architectural design pattern (ADP). It consists largely of the application of new cloud-based technology to the same requirements and constraints.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

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Data Warehouse Design: How To Structure Your Data Assets

ScienceSoft

Explore what architectural approaches are employed to design a data warehouse and choose what DWH structure is beneficial for your business.

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How to Launch First Amazon Elastic MapReduce (EMR)?

Analytics Vidhya

Introduction Amazon Elastic MapReduce (EMR) is a fully managed service that makes it easy to process large amounts of data using the popular open-source framework Apache Hadoop. EMR enables you to run petabyte-scale data warehouses and analytics workloads using the Apache Spark, Presto, and Hadoop ecosystems.

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Metadata-Driven Data Warehouses are Ideal

TDAN

A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.

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Manage your data warehouse cost allocations with Amazon Redshift Serverless tagging

AWS Big Data

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. To create custom reports for your cost and usage data, complete the following steps: On the AWS Cost Management console, choose Reports in the navigation pane. Choose Create new report.