Any enterprise looking to stay competitive must consider leveraging knowledge graphs and LLMs to unlock the value hidden within their data. This article unpacks the latest research and business implications.
Accelerating Your Data Innovation Journey in Healthcare
Continue the data innovation adventure with Ryan Sousa's series, "Accelerating Your Data Innovation Journey in Healthcare." Explore Sousa's recommended self-service analytics tools and some high-impact use cases in the industry.
We now know technology alone isn’t the solution and are led to think that culture is the biggest obstacle to analytics adoption. But that’s a sloppy excuse. Read why.
In the third installment of Parul Pandey’s AI risk management series, we explore various strategies and practices beyond traditional model risk management.
IIA's roundup of the best articles from around the web, curated and contextualized by unbiased analytics experts at IIA.
In the second article in our AI risk management series, we pivot our focus to a vital element in the context of ML systems: organizational processes.
This article introduces a three-part series on AI risk management. It discusses cultural competencies that can prevent and mitigate AI incidents, with a focus on promoting responsible AI practices.
As Vinita Bansal’s job shifted from coding to managing people, and then managing managers, she gleaned five crucial lessons through experimentation, trial, and error.
As your company maps out its 2024 AI strategy, use this powerful metaphor to consider the implications of centralized knowledge and striking a balance between knowledge graphs and LLMs.