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Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift

AWS Big Data

Customers across industries are becoming more data driven and looking to increase revenue, reduce cost, and optimize their business operations by implementing near real time analytics on transactional data, thereby enhancing agility. In the Instance configuration section , select Memory optimized classes.

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Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift

AWS Big Data

read replicas, federated query, analytics accelerators) Move the data to a data store optimized for running analytical queries such as a data warehouse The zero-ETL integration is focused on simplifying the latter approach. They would like to get these metrics in near-real time using a zero-ETL integration. or higher version) database.

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Unlock insights on Amazon RDS for MySQL data with zero-ETL integration to Amazon Redshift

AWS Big Data

The data becomes available in Amazon Redshift within seconds, allowing you to use the analytics features of Amazon Redshift and capabilities like data sharing, workload optimization autonomics, concurrency scaling, machine learning, and many more. They would like to get these metrics in near real time using a zero-ETL integration.

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Simplify AWS Glue job orchestration and monitoring with Amazon MWAA

AWS Big Data

Analytics professionals are tasked with deriving value from data stored in these distributed systems to create better, secure, and cost-optimized experiences for their customers. A common use case with this data would be to gather usage metrics on principals acting on your account’s resources for auditing and regulatory needs.