
Machine Learning Lifecycle, Part 1: Deployment
In this multi-part series, the author begins at the final stage of the machine learning lifecycle: deployment. Explore key challenges, deployment patterns, and degrees of automation.
In this multi-part series, the author begins at the final stage of the machine learning lifecycle: deployment. Explore key challenges, deployment patterns, and degrees of automation.
IIA clients want to know more about agentic AI. This article elaborates on the multi-agent system and how it operates
Data literacy is not enough. We need data instrumentation. Read this article to rethink your approach to data literacy in an information economy.
IIA Roundtable Peer Insights
Read the key takeaways from IIA’s roundtable discussion on how companies approached AI in 2024 and their key challenges moving forward.
IIA Roundtable Peer Insights
Read key insights from IIA’s roundtable discussion on defining, measuring, and prioritizing enterprise AI initiatives.
Accelerating Your Data Innovation Journey in Healthcare
In Part 14 of our series on data innovation in healthcare, Ryan Sousa examines how Children’s Minnesota accelerated their data and analytics capabilities and created a data-driven culture.
What is your analytics leadership style? Read this thoughtful reflection from an analytics leader to inspire your own.
IIA Roundtable Peer Insights
Read the key takeaways from IIA’s roundtable discussion on building internal analytics conferences.