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Stream and Event Processing Require Real-Time Analytics

David Menninger's Analyst Perspectives

In my past perspectives, I’ve written about the evolution from data at rest to data in motion and the fact that you can’t rely on dashboards for real-time analytics. Organizations are becoming more and more event-driven and operating based on streaming data.

Analytics 252
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DCO Government Highlights Data-Driven Innovation in the Public Sector

Corinium

This two-day digital event shone a spotlight on the most innovative data strategies, data-driven cultures and digital transformations in the US public sector.

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Maximizing your event-driven architecture investments: Unleashing the power of Apache Kafka with IBM Event Automation

IBM Big Data Hub

Recognizing the need to harness real-time data, businesses are increasingly turning to event-driven architecture (EDA) as a strategic approach to stay ahead of the curve. This trend grows stronger as organizations realize the benefits that come from the power of real-time data streaming.

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Real-time artificial intelligence and event processing  

IBM Big Data Hub

By leveraging AI for real-time event processing, businesses can connect the dots between disparate events to detect and respond to new trends, threats and opportunities. AI and event processing: a two-way street An event-driven architecture is essential for accelerating the speed of business.

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Real-time transaction data analysis with IBM Event Automation

IBM Big Data Hub

1] The need to improve real-time decision-making is contributing to a growing demand for event-driven solutions and their ability to help businesses achieve continuous intelligence and situation awareness. An event-driven architecture focuses on the publication, capture, processing and storage of events.

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Build event-driven data pipelines using AWS Controllers for Kubernetes and Amazon EMR on EKS

AWS Big Data

An event-driven architecture is a software design pattern in which decoupled applications can asynchronously publish and subscribe to events via an event broker. For big data processing, which requires distributed computing, you can use Spark on Amazon EKS.

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The winning combination for real-time insights: Messaging and event-driven architecture

IBM Big Data Hub

In order to stay ahead, businesses need to enable proactive decision making—and this stems from building an IT infrastructure that provides the foundation for the availability of real-time data. The core of building this real-time responsiveness lies in messaging, but its value can be expanded through event-driven architectures.