Remove Data Architecture Remove Data Warehouse Remove Structured Data
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Incremental refresh for Amazon Redshift materialized views on data lake tables

AWS Big Data

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. However, if you want to test the examples using sample data, download the sample data. Amazon Redshift delivers price performance right out of the box.

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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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Ingest data from Google Analytics 4 and Google Sheets to Amazon Redshift using Amazon AppFlow

AWS Big Data

Amazon AppFlow automatically encrypts data in motion, and allows you to restrict data from flowing over the public internet for SaaS applications that are integrated with AWS PrivateLink , reducing exposure to security threats. He has worked with building data warehouses and big data solutions for over 13 years.

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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.

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Snowflake: A New Blueprint for the Modern Data Warehouse

CDW Research Hub

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Need for a data mesh architecture Because entities in the EUROGATE group generate vast amounts of data from various sourcesacross departments, locations, and technologiesthe traditional centralized data architecture struggles to keep up with the demands for real-time insights, agility, and scalability.

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