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From data lakes to insights: dbt adapter for Amazon Athena now supported in dbt Cloud

AWS Big Data

The need for streamlined data transformations As organizations increasingly adopt cloud-based data lakes and warehouses, the demand for efficient data transformation tools has grown. Using Athena and the dbt adapter, you can transform raw data in Amazon S3 into well-structured tables suitable for analytics.

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MongoDB Enhances Developer Data Platform

David Menninger's Analyst Perspectives

These include architectural optimizations to reduce memory usage and query times with more efficient batch processing to deliver better throughput, faster bulk writes and accelerated concurrent writes during data replication. also delivers enhanced developer-centric features focused on the development of AI applications.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. datazone_env_twinsimsilverdata"."cycle_end";')

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What is data architecture? A framework to manage data

CIO Business Intelligence

Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data.

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The Internet of Things: Real-Time Data and Analytics Enable Business Innovation

David Menninger's Analyst Perspectives

The emerging internet of things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere.

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Migrate Delta tables from Azure Data Lake Storage to Amazon S3 using AWS Glue

AWS Big Data

We often see requests from customers who have started their data journey by building data lakes on Microsoft Azure, to extend access to the data to AWS services. In such scenarios, data engineers face challenges in connecting and extracting data from storage containers on Microsoft Azure.

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Apache Iceberg optimization: Solving the small files problem in Amazon EMR

AWS Big Data

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.