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The top four log analytics and log management best practices

Dynatrace

By following key log analytics and log management best practices, teams can get more business value from their data. Challenges driving the need for log analytics and log management best practices As organizations undergo digital transformation and adopt more cloud computing techniques, data volume is proliferating.

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Enhancing Azure data analytics and Azure observability with Dynatrace Grail

Dynatrace

Azure observability and Azure data analytics are critical requirements amid the deluge of data in Azure cloud computing environments. As digital transformation accelerates and more organizations are migrating workloads to Azure and other cloud environments, they need observability and data analytics capabilities that can keep pace.

Azure 179
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Dynatrace enhances Business Analytics with business events powered by Grail

Dynatrace

Following the launch of Dynatrace® Grail for Log Management and Analytics , we’re excited to announce a major update to our Business Analytics solution. Since they rely on capabilities designed for IT monitoring, they inherit a series of architectural design constraints that limit their usefulness.

Analytics 230
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Expanded Grail data lakehouse and new Dynatrace user experience unlock boundless analytics

Dynatrace

Grail – the foundation of exploratory analytics Grail can already store and process log and business events. Let Grail do the work, and benefit from instant visualization, precise analytics in context, and spot-on predictive analytics. You no longer need to split, distribute, or pre-aggregate your data.

Analytics 229
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How unified data and analytics offers a new approach to software intelligence

Dynatrace

IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. With a data and analytics approach that focuses on performance without sacrificing cost, IT pros can gain access to answers that indicate precisely which service just went down and the root cause. Real-time anomaly detection.

Analytics 191
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Dynatrace OpenPipeline: Stream processing data ingestion converges observability, security, and business data at massive scale for analytics and automation in context

Dynatrace

By putting data in context, OpenPipeline enables the Dynatrace platform to deliver AI-driven insights, analytics, and automation for customers across observability, security, software lifecycle, and business domains. This “data in context” feeds Davis® AI, the Dynatrace hypermodal AI , and enables schema-less and index-free analytics.

Analytics 194
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Data privacy by design: How an observability platform protects data security

Dynatrace

Creating an ecosystem that facilitates data security and data privacy by design can be difficult, but it’s critical to securing information. When organizations focus on data privacy by design, they build security considerations into cloud systems upfront rather than as a bolt-on consideration.

Design 191