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How to evaluate modern APM solutions

Dynatrace

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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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. More than mere support.

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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. Retain data.

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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

However, organizations must structure and store data inputs in a specific format to enable extract, transform, and load processes, and efficiently query this data. This approach enables organizations to use this data to build artificial intelligence (AI) and machine learning models from large volumes of disparate data sets.

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RPA Vs Test Automation

Testsigma

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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Generative AI in the Enterprise

O'Reilly

Users and Nonusers AI adoption is in the process of becoming widespread, but it’s still not universal. Until AI reaches 100%, it’s still in the process of adoption. Automating the process of building complex prompts has become common, with patterns like retrieval-augmented generation (RAG) and tools like LangChain.

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When should enterprises choose codeless automation for testing?

Testsigma

Instead, it relies on natural language processing , drag-and-drop UI elements , artificial intelligence, self-healing capabilities etc. Definitely, it comes with certain limitations and is not 100% perfect. Choosing a tool is not a textbook process. Codeless testing and its advantage – a brief introduction.

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