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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

In this example, we use Amazon EMR Serverless in combination with the open source library Pydeequ to act as an external system for data quality. If the asset has AWS Glue Data Quality enabled, you can now quickly visualize the data quality score directly in the catalog search pane.

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How Klarna Bank AB built real-time decision-making with Amazon Kinesis Data Analytics for Apache Flink

AWS Big Data

This post presents a reference architecture for real-time queries and decision-making on AWS using Amazon Kinesis Data Analytics for Apache Flink. In addition, we explain why the Klarna Decision Tooling team selected Kinesis Data Analytics for Apache Flink for their first real-time decision query service.

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Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 1

AWS Big Data

Amazon Managed Service for Apache Flink , formerly known as Amazon Kinesis Data Analytics, is the AWS service offering fully managed Apache Flink. Each of the distributed components of an application asynchronously snapshots its state to an external persistent datastore. This is a two-phase operation.

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

In this post, we discuss ways to modernize your legacy, on-premises, real-time analytics architecture to build serverless data analytics solutions on AWS using Amazon Managed Service for Apache Flink. In this traditional architecture, a relational database is used to store data from streaming data sources.

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Enable Multi-AZ deployments for your Amazon Redshift data warehouse

AWS Big Data

Originally published on December 9th, 2022. Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Choose the Maintenance Select a snapshot and choose Restore snapshot , Restore to provisioned cluster. See the required steps as below.

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Reliable Data Exchange with the Outbox Pattern and Cloudera DiM

Cloudera

The Outbox Pattern The general idea behind this pattern is to have an “outbox” table in the service’s data store. When the service receives a request, it not only persists the new entity, but also a record representing the message that will be published to the event bus. It is implemented in Java using the Spring framework.

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AWS Glue streaming application to process Amazon MSK data using AWS Glue Schema Registry

AWS Big Data

Organizations across the world are increasingly relying on streaming data, and there is a growing need for real-time data analytics, considering the growing velocity and volume of data being collected. Upon success, update the AWS Glue Data Catalog table using the updated schema. page in the GitHub repository. $