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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 193
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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. This goal isn’t limited to observability efforts. Grail architectural basics.

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Probabilistic Data Structures for Web Analytics and Data Mining

Highly Scalable

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. This approach often leads to heavyweight high-latency analytical processes and poor applicability to realtime use cases. bits per unique value.

Analytics 191
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How Our Paths Brought Us to Data and Netflix

The Netflix TechBlog

Part of our series on who works in Analytics at Netflix?—?and Over the course of the four years it became clear that I enjoyed combining analytical skills with solving real world problems, so a PhD in Statistics was a natural next step. Photo from a team curling offsite? I then transitioned to a full industry role at Netflix.

Analytics 230
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Flexible, scalable, self-service Kubernetes native observability now in General Availability

Dynatrace

Of course, the most important aspect of activating Dynatrace on Kubernetes is the incalculable level of value the platform unlocks. Of course, everything is deployed using standard kubectl commands. This solution offers both maximum efficiency and adherence for the toughest privacy or compliance demands.

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Upgrade to the Data explorer to level up your data visualizations and analysis

Dynatrace

We believe that the two worlds of automated (AIOps) and manual (dashboards) data analytics are complementary rather than contradictory. Of course, adequate solutions for both worlds exist, However, we argue that even today, they either lack the ease of use or smartness required by today’s complex cloud ecosystems.

Metrics 227
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My (Seemingly) Random Walk to Netflix

The Netflix TechBlog

Part of our series on who works in Analytics at Netflix?—?and Upon graduation, they received an offer from Netflix to become an analytics engineer, and pursue their lifelong dream of orchestrating the beautiful synergy of analytics and entertainment. That person grew up dreaming of working in the entertainment industry.