Real-time Analytics News for the Week Ending April 19
In this week's real-time analytics news: NVIDIA announced that it will build AI supercomputers entirely in the U.S.
Topic: Analytics
How real-time data is used in business analytics, including predictive, descriptive, and prescriptive uses. Edge analytics is also explored.
The Power of Visual Analytics in Industry
As the volume of video data continues to grow, the ability to understand and act on it — in real time — will become a competitive differentiator across …
Simplifying AI Decision-Making with a New Planning Tool
The development of L-MAP is a step forward in making automated decision-making more reliable and efficient in complex scenarios. The tool could greatly benefit …
After 40+ Years of Spreadsheets, Do They Still Make Sense?
The growing need for real-time insights and the rise of IT consolidation may relegate spreadsheets from a mainstream tool to one that supports a more …
AI Brings Manufacturing into the Real-Time Realm
Factory managers need reliable data to drive real-time analytics and AI-driven insights of their manufacturing
Real-time Analytics News for the Week Ending April 5
In this week's real-time analytics news: The latest round of MLCommons Inference benchmark tests show that hardware and software advances optimized for …
Real-time Analytics News for the Week Ending March 29
In this week's real-time analytics news: AWS expands access to expert-level analysis via natural language processing.
The End of Shadow IT in Automation: Why Business Logic and Orchestration Logic Must Converge
For organizations looking to scale automation beyond IT, the path forward is clear: stop creating more silos and start connecting business logic with …
The Economic Impact of AI Agents in Industrial Operations
AI agents are poised to become a foundational element of industrial operations, offering enhanced productivity, agility, and sustainability.
How Data and AI Improve Troubleshooting Workflows to Solve Problems Quickly
As industrial operations grow more complex, traditional troubleshooting methods are no longer sufficient. Organizations must embrace AI-driven, data-rich …