Remove Architecture Remove Artificial Intelligence Remove Healthcare Remove Processing
article thumbnail

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. Software project managers can optimize development processes by analyzing workflow data, such as development time, code commits, and testing phases. Government.

article thumbnail

What is explainable AI? The key to closing the AI confidence gap

Dynatrace

Explainable AI is an aspect of artificial intelligence that aims to make AI more transparent and understandable, resulting in greater trust and confidence from the teams benefitting from the AI. In a perfect world, a robust AI model can perform complex tasks while users observe the decision process and audit any errors or concerns.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. The Greenplum Architecture. The Greenplum Architecture.

Big Data 321
article thumbnail

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.

article thumbnail

AWS Re:Invent 2021 guide: Multicloud modernization and digital transformation

Dynatrace

Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. These tools simply can’t provide the observability needed to keep pace with the growing complexity and dynamism of hybrid and multicloud architecture.

AWS 219
article thumbnail

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. CloudOps includes processes such as incident management and event management. The four stages of data processing. Aggregate it for alerts.

DevOps 185