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Advanced analytics: Leverage edge IoT data with OpenTelemetry and Dynatrace

Dynatrace

In today’s data-driven world, businesses across various industry verticals increasingly leverage the Internet of Things (IoT) to drive efficiency and innovation. IoT is transforming how industries operate and make decisions, from agriculture to mining, energy utilities, and traffic management.

IoT 264
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How executives reveal breakthrough insights into customer experiences with Dynatrace to accelerate business growth

Dynatrace

Key insights for executives: Optimize customer experiences through end-to-end contextual analytics from observability, user behavior, and business data. Consolidate real-user monitoring, synthetic monitoring, session replay, observability, and business process analytics tools into a unified platform. Google or Adobe Analytics).

Analytics 286
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Visualizing IoT Data With MQTT, QuestDB, and Grafana

DZone

Monitoring Time-Series IoT Device Data Time-series data is crucial for IoT device monitoring and data visualization in industries such as agriculture, renewable energy, and meteorology. It enables trend analysis, anomaly detection, and predictive analytics, empowering businesses to optimize performance and make data-driven decisions.

IoT 241
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What is behavior analytics?

Dynatrace

As user experiences become increasingly important to bottom-line growth, organizations are turning to behavior analytics tools to understand the user experience across their digital properties. Here’s what these analytics are, how they work, and the benefits your organization can realize from using them.

Analytics 246
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DYOC: Agentless RUM, OpenKit, Metric ingest, and Business Analytics

Dynatrace

In fact, Dynatrace customers use OpenKit to monitor many digital touchpoints like ATMs, kiosks, and IoT devices. Now we have performance and errors all covered: Business Analytics. Digital Business Analytics can help answer those questions. Contact your Dynatrace Sales Engineer for a demo or POC of DEM and Business Analytics.

Analytics 200
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

Kafka is optimized for high-throughput event streaming , excelling in real-time analytics and large-scale data ingestion. Its architecture supports stream transformations, joins, and filtering, making it a powerful tool for real-time analytics. Apache Kafka uses a custom TCP/IP protocol for high throughput and low latency.

Latency 147
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How Edge and Industrial IoT Will Converge in 2025: A New Era for Smart Manufacturing

VoltDB

The Need for Real-Time Analytics and Automation With increasing complexity in manufacturing operations, real-time decision-making is essential. With predictive analytics at the edge, machines can be monitored continuously for early signs of wear, allowing for timely maintenance without interrupting production.

IoT 52