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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. For Available versions , choose Aurora MySQL 3.03.1 (or or higher). For Templates , select Production.

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Bionic Eye, Disease Control, Time Crystal Research Powered by IO500 Top Storage Systems

CIO Business Intelligence

The concept of a time crystal was first offered in 2012 by Frank Wilczek, a theoretical physicist, mathematician, and Nobel laureate. . To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

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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. For DB instance identifier , enter zero-etl-source-rms. Choose Create policy.

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Simplify external object access in Amazon Redshift using automatic mounting of the AWS Glue Data Catalog

AWS Big Data

For instructions, see Change the default permission model. For instructions, see Upgrading AWS Glue data permissions to the AWS Lake Formation model. The security setup (setting up the permissions model or data governance) is owned by account and database administrators. Change the settings for existing Data Catalog resources.

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Introduction to Conditional Random Fields

Edwin Chen

Imagine you have a sequence of snapshots from a day in Justin Bieber’s life, and you want to label each image with the activity it represents (eating, sleeping, driving, etc.). One way is to ignore the sequential nature of the snapshots, and build a per-image classifier. Randomly initialize the weights of our CRF model.