Why Training LLMs on Company-Owned Data Is the Key to Scaling AI
Training LLMs on company-owned data equips an organization’s LLMs with the intelligence they need to act as true extensions of an
Topic: Big Data
Big Data technologies and use cases for real-time analytics. Big Data technologies, market insights, and use cases for real-time analytics.
Real-time Analytics News for the Week Ending May 10
In this week's real-time analytics news: IBM announced a number of new technologies to scale enterprise
Why Data Literacy Is Key to Unlocking AI Innovation
Bridging the gap between AI potential and real-world impact requires a strategic investment in data literacy. Organizations that train their workforce, …
Real-time Analytics News for the Week Ending April 26
In this week's real-time analytics news: MIT focuses on making AI-generated code more accurate in any
Transforming Data Chaos into Clarity with A Semantic Layer
As BI applications embrace Gen AI, the clarion call for providing them with well-defined data becomes even more pertinent. With a robust semantic layer that …
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
How AI Enhances Master Data Accuracy in Enterprise ERP Systems
Key advancements in AI-powered master data management within ERP systems enhances data accuracy, streamline business operations, and improves decision-making …
Building an Internal Data Marketplace That Delivers: 10 Essential Steps for Success
An internal data marketplace is the missing handshake between builders and consumers. Following these critical steps for building a marketplace will empower …
Data vs. Metadata: The Overlooked Challenge in Data Management
As organizations continue to rely on data for critical operations and innovation, effective metadata management will be essential for ensuring accuracy, …
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 …