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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

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. This “data in context” feeds Davis® AI, the Dynatrace hypermodal AI , and enables schema-less and index-free analytics.

Analytics 193
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Business analytics tools: Use cases and best practices for IT business analytics

Dynatrace

Leveraging business analytics tools helps ensure their experience is zero-friction–a critical facet of business success. How do business analytics tools work? Business analytics begins with choosing the business KPIs or tracking goals needed for a specific use case, then determining where you can capture the supporting metrics.

Analytics 173
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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. This is only possible because of our no-index approach and massive parallel processing capabilities, which enable Dynatrace to offer extra-long data retention (15+ months) at full granularity that is cost-efficient and fast.

Analytics 229
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Automate your work with unified observability and custom solutions

Dynatrace

Automate disk resizing operations with Davis AI predictive analytics The Dynatrace Site Reliability Engineering (SRE) team was looking for a way to automatically adjust disk space for cloud volumes on a regular basis to avoid over- or under-provisioning them. Figure 3: Funnel analysis implemented by selecting a custom user journey.

AWS 219
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The history of Grail: Why you need a data lakehouse

Dynatrace

Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. Ingest and process with Grail. Grail architectural basics. Retain data.

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Microsoft Azure digital transformation: Embracing the power of cloud technology with next-gen observability

Dynatrace

This massive migration is critical to organizations’ digital transformation , placing cloud technology front and center and elevating the need for greater visibility, efficiency, and scalability delivered by a unified observability and security platform. This creates a billing process that is simplified and straightforward.

Azure 171
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What is a Distributed Storage System

Scalegrid

This process effectively duplicates essential parts of information to safeguard against potential loss. It utilizes methodologies like DStore, which takes advantage of underused hard drive space by using it for storing vast amounts of collected datasets while enabling efficient recovery processes.

Storage 130