Report: Industrial AI Poised for Rapid Growth
Most industrial organizations now have CEO-driven industrial AI strategies, reflecting a shift from experimentation to enterprise-wide
Topic: Analytics
How real-time data is used in business analytics, including predictive, descriptive, and prescriptive uses. Edge analytics is also explored.
Real-time Analytics News for the Week Ending October 11
In this week's real-time analytics news: Google Cloud launched Gemini Enterprise, an agentic platform designed to bring the full power of Google’s AI to …
Data Fluency: The Foundation for AI in Insurance
The future of insurance will be shaped by those who treat data as a living, strategic asset and not simply a byproduct of
Why Real-Time Data is Imperative for Intelligent Experiences
Intelligent experiences depend on predicting what help or information a user will want before they ask and then act on that prediction.
Vibe Coding: How AI-First Workflows Are Redefining Customer Data Engineering
In customer data engineering, speed and quality have historically been at odds. Vibe coding changes that equation. By enabling engineers to work at the level …
Real-time Analytics News for the Week Ending September 27
In this week's real-time analytics news: Google Cloud announced new AI-native capabilities to help data scientists and developers build intelligent, autonomous …
Real-time Analytics News for the Week Ending September 20
In this week's real-time analytics news: NVIDIA and Intel Corporation announced a collaboration to jointly develop custom data center and PC products to …
The Revenue AI Imperative: Connecting Data, Context, and Guided Selling in Real Time
For enterprise revenue AI to work, it needs more than data. It needs context. Without it, accuracy breaks, decisions stall, and trust disappears. Here’s how …
How AI Enhances Predictive Analytics
Companies moving to AI-powered predictive analytics are reporting measurable gains and leading firms are documenting robust
How Kafka and Edge Processing Enable Real-Time Decisions
By pairing Kafka with adaptive edge processing, organizations achieve the best of both worlds: instantaneous local decisions and enterprise-wide