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Causal AI use cases for modern observability that can transform any business

Dynatrace

Artificial intelligence adoption is on the rise everywhere—throughout industries and in businesses of all sizes. Healthcare. For example, causal AI can help public health officials better understand the effects of environmental factors, healthcare policies, and social factors on health outcomes.

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Four observability trends IT leaders should have on the radar in 2023

Dynatrace

Just as the world began to emerge from the immediate effects of an unprecedented global healthcare crisis, it faced yet another emergency. However, the growing awareness of the potential for bias in artificial intelligence will be a barrier to widespread automation in business operations, IT, development, and security.

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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. What Exactly is Greenplum? At a glance – TLDR.

Big Data 321
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AWS Re:Invent 2021 guide: Multicloud modernization and digital transformation

Dynatrace

In fact, Gartner predicts that cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives by 2025 — up from less than 40% in 2021. These modern, cloud-native environments require an AI-driven approach to observability. At AWS re:Invent 2021 , the focus is on cloud modernization.

AWS 230
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Applying real-world AIOps use cases to your operations

Dynatrace

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. Like all AI applications, whether in manufacturing, healthcare, finance, or other industries, AIOps is not about reducing the human factor’s importance.

DevOps 198
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Generative AI in the Enterprise

O'Reilly

Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking. This is an area where cloud providers already bear much of the burden, and will continue to bear it in the future.