Remove Cost-Benefit Remove Data Warehouse Remove Machine Learning
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

The following requirements were essential to decide for adopting a modern data mesh architecture: Domain-oriented ownership and data-as-a-product : EUROGATE aims to: Enable scalable and straightforward data sharing across organizational boundaries. Eliminate centralized bottlenecks and complex data pipelines.

IoT 100
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Cloudera Data Warehouse Demonstrates Best-in-Class Cloud-Native Price-Performance

Cloudera

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. With pay-as-you-go pricing, platforms that deliver high-performance benefit users not only through faster results but also through direct cost savings.

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What is a Data Mesh?

DataKitchen

DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . This post (1 of 5) is the beginning of a series that explores the benefits and challenges of implementing a data mesh and reviews lessons learned from a pharmaceutical industry data mesh example.

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

AWS Big Data

At AWS re:Invent 2024, we announced the next generation of Amazon SageMaker , the center for all your data, analytics, and AI. In this post, we explore the benefits of SageMaker Unified Studio and how to get started. We are excited to announce the general availability of SageMaker Unified Studio.

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Migrate a petabyte-scale data warehouse from Actian Vectorwise to Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Solution overview Amazon Redshift is an industry-leading cloud data warehouse.

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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. In practice, OTFs are used in a broad range of analytical workloads, from business intelligence to machine learning.

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Is Google BigQuery The Future Of Big Data Analytics?

Smart Data Collective

Certain big data systems can be used to automatically bring this information together (such as through the use of BigQuery integration ). Customer experience is another key area that can benefit from big data analytics. The operational side of your business could benefit greatly as well. Big data analytics advantages.

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