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Recap of Amazon Redshift key product announcements in 2024

AWS Big Data

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

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Cloudera Data Warehouse outperforms Azure HDInsight in TPC-DS benchmark

Cloudera

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . benchmark.

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Accelerate analytics and AI innovation with the next generation of Amazon SageMaker

AWS Big Data

Governance features including fine-grained access control are built into SageMaker Unified Studio using Amazon SageMaker Catalog to help you meet enterprise security requirements across your entire data estate. With SageMaker Unified Studio, this entire process can now be carried out within a single data and AI development environment.

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Integrating Data Governance and Enterprise Architecture

erwin

Why should you integrate data governance (DG) and enterprise architecture (EA)? Two of the biggest challenges in creating a successful enterprise architecture initiative are: collecting accurate information on application ecosystems and maintaining the information as application ecosystems change.

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Write queries faster with Amazon Q generative SQL for Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed, AI-powered cloud data warehouse that delivers the best price-performance for your analytics workloads at any scale. This will take a few minutes to run and will establish a query history for the tpcds data. Choose Run all on each notebook tab.

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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

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Fauna’s Data Platform Combines Agility and Transaction Integrity

David Menninger's Analyst Perspectives

Traditionally, operational data platforms support applications used to run the business. Data is then extracted and loaded into analytic data platforms for analysis. The emergence of intelligent applications does not eradicate the use of specialist analytic data platforms, such as data warehouses and data lakehouses.