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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. Internally, Apache Flink uses clever mechanisms to maintain exactly-once state consistency, while also optimizing for throughput and reduced latency.

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Real-time cost savings for Amazon Managed Service for Apache Flink

AWS Big Data

When running Apache Flink applications on Amazon Managed Service for Apache Flink , you have the unique benefit of taking advantage of its serverless nature. This means that cost-optimization exercises can happen at any time—they no longer need to happen in the planning phase.

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Generative AI’s change management challenge

CIO Business Intelligence

Despite headlines warning that artificial intelligence poses a profound risk to society , workers are curious, optimistic, and confident about the arrival of AI in the enterprise, and becoming more so with time, according to a recent survey by Boston Consulting Group (BCG). For many, their feelings are based on sound experience.

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Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 2

AWS Big Data

Unaligned checkpoints help, under specific conditions, to reduce checkpointing time for applications suffering temporary backpressure, and can be now enabled in Amazon Managed Service for Apache Flink applications running Apache Flink 1.15.2 This feature has been available since Apache Flink 1.11 and has received many improvements since then.

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Integrating AI into Asset Performance Management: It’s all about the data

IBM Big Data Hub

Imagine a future where artificial intelligence (AI) seamlessly collaborates with existing supply chain solutions, redefining how organizations manage their assets. But what if you could optimize even further? Let’s look at some of those challenges to generative AI for asset performance management. Undoubtedly.

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The art and science of data product portfolio management

AWS Big Data

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. How do we define “risk” and “value” in the context of data products, and how can we measure this?

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Data Maturity Models | Measure The Health Of Your Data

Anmut

Data maturity models are frameworks that help you understand how reliable, efficient, and effective your organisation is at managing data. These models place you on a maturity scale that is broken up into stages, often 1 to 5, and as your organisation improves its data management , you progress to the following stage.