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Frictionless retail: A pandemic imperative for IT

Dynatrace

For most who work in the retail sector, the pandemic has been an unwelcome test of our ability to cope with disruption. In eight months, retailers offering curbside pickup increased from 7% to 44%, reflecting rapidly changing consumer preferences. Let’s illustrate a simple use case for a retail outlet. Dynatrace news.

Retail 133
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Intelligent, context-aware AI analytics for all your custom metrics

Dynatrace

Dynatrace recently opened up the enterprise-grade functionalities of Dynatrace OneAgent to all the data needed for observability, including metrics, events, logs, traces, and topology data. Davis topology-aware anomaly detection and alerting for your custom metrics. Seamlessly report and be alerted on topology-related custom metrics.

Metrics 245
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Dynatrace and Red Hat expand enterprise observability to edge computing

Dynatrace

As an example, many retailers already leverage containerized workloads in-store to enhance customer experiences using video analytics or streamline inventory management using RFID tracking for improved security. In this case, Davis finds that a Java Spring Micrometer metric called Failed deliveries is highly correlated with CPU spikes.

Retail 258
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Extend business observability: Extract business events from online databases (Part 1)

Dynatrace

Dynatrace business events provide precise, real-time business metrics that support fine-grained business decisions and auditable business reporting. We also looked at a pizza chain example, connecting each customer order to the fulfillment process milestones that followed, including the handoff to the delivery agent.

Database 226
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Pioneering customer-centric pricing models: Decoding ingest-centric vs. answer-centric pricing

Dynatrace

retail giant, initially tied to an ingest-centric pricing vendor, found itself manually curbing costs by limiting daily log ingestion to 3 TB and reducing retention periods. Consequently, the company’s mean time to identify (MTTI) and mean time to resolve (MTTR) during peak retail seasons was too slow. A prominent U.S. Smart defaults.

Retail 237
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Causal AI use cases for modern observability that can transform any business

Dynatrace

For example, machine learning can identify correlations in data and generate predictions, while causal AI determines which ones are the true drivers. For example, causal AI can help public health officials better understand the effects of environmental factors, healthcare policies, and social factors on health outcomes.

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Extend business observability: Extract business events from online databases (Part 1)

Dynatrace

Dynatrace business events provide precise, real-time business metrics that support fine-grained business decisions and auditable business reporting. We also looked at a pizza chain example, connecting each customer order to the fulfillment process milestones that followed, including the handoff to the delivery agent.

Database 130