DZone

JULY 11, 2023

Artificial Intelligence: Definition and Practical Applications Artificial intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence. The uses of artificial intelligence are vast and continue to expand across various industries.

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Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. This data lands in its original, raw form without requiring schema definition.

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Dynatrace

OCTOBER 4, 2022

Further, it builds a rich analytics layer powered by Dynatrace causational artificial intelligence, Davis® AI, and creates a query engine that offers insights at unmatched speed. As a result, we created Grail with three different building blocks, each serving a special duty: Ingest and process. Ingest and process with Grail.

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Dynatrace

NOVEMBER 1, 2022

All these definitions are distinct and important. Most IT incident management systems use some form of the following metrics to handle incidents efficiently and maintain uninterrupted service for optimal customer experience. It shows how efficiently your DevOps team is at quickly diagnosing a problem and implementing a fix.

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Testsigma

MARCH 12, 2021

Robotic Process Automation and Test Automation are two confusing terms in testing processes. Similar to TDD and BDD processes, RPA and test automation seem like a single branch of the test segment which is common to be exchanged in communication during planning. What is Robotic Process Automation (RPA)? Source: [link].

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Dynatrace

NOVEMBER 8, 2021

G2 Research includes a clear definition of APM in its Grid Report for Application Performance Monitoring for Spring 2021. These solutions provide performance metrics for applications, with specific insights into the statistics, such as the number of transactions processed by the application or the response time to process such transactions.

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All Things Distributed

SEPTEMBER 4, 2017

In the case of artificial intelligence (AI) and machine learning (ML), this is different. And thirdly, an "algorithmic revolution" has taken place, meaning it is now possible to train trillions of algorithms simultaneously, making the whole machine learning process much faster. Progress through machine learning.

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