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Our most critical mission: Adopting AI

Dynatrace

Artificial Intelligence (AI) is a complex, rapidly growing technology. In a recent FedScoop panel Brett Vaughn, Navy Chief AI Officer, and Willie Hicks, Federal CTO for Dynatrace discuss this up-and-coming technology including: Their definition of AI. Dynatrace news. How AI is used in the Navy.

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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. High-performance analytics—no indexing required. Start using Grail now.

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How to evaluate modern APM solutions

Dynatrace

Organizations use APM to ensure system availability, optimize service performance and response times, and improve user experiences. G2 Research includes a clear definition of APM in its Grid Report for Application Performance Monitoring for Spring 2021. Artificial intelligence for IT operations (AIOps) for applications.

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RPA Vs Test Automation

Testsigma

While it is definitely true that both of these processes automate the process, “what” and “how” of their automation is entirely different. Surprisingly, this definition fits perfectly with RPA by making slight adjustments. The word “automation” seems to be a culprit in this case. What is Test Automation?

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What is APM?

Dynatrace

Practitioners use APM to ensure system availability, optimize service performance and response times, and improve user experiences. Even a conflict with the operating system or the specific device being used to access the app can degrade an application’s performance. User experience and business analytics.

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Rethinking the 'production' of data

All Things Distributed

Developments like cloud computing, the internet of things, artificial intelligence, and machine learning are proving that IT has (again) become a strategic business driver. Marketers use big data and artificial intelligence to find out more about the future needs of their customers. This pattern should be broken.

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Generative AI in the Enterprise

O'Reilly

AI users are definitely facing these problems: 7% report that data quality has hindered further adoption, and 4% cite the difficulty of training a model on their data. Several respondents also mentioned working with video: analyzing video data streams, video analytics, and generating or editing videos.