The Modern Data and DataOS Blog

Ontology, Knowledge Graph, Semantic Layer: What’s the Difference?

The Hard Questions Enterprise Leaders are Asking About AI

Speed to Conviction: Rethinking Experimentation in the AI Era

Customer 360 AI: Personalization at Scale

What The Modern Data Report’s 5 Emerging Trends Mean for the Public Sector

The Modern Data Company Launches DataOS for Public Sector at the State of Texas DIR Innovation Lab for Demonstrations

The Context Layer for Defensible AI in Financial Services

How AI Raises the Standard for Data

How to Reduce LLM Token Costs at the Data Layer

It’s Time to Rethink Consulting-Led Data Modernization

Your Data Pipeline Is Not a Data Product

AI Agents Are Advancing Faster Than Enterprise Data Is Ready for Them

The Economics of Agentic Al: You Can't Control Costs You Can't Trace

Token Economics: Why Value Per Token Matters More Than Token Cost

The Semantic Layer and Governance a “Company Brain” Needs

The Data Debt You Can't See On a Dashboard

Why Your Data Platform Isn't Wired for AI

The Modern Data Company Achieves TX-RAMP Level 2 Certification for DataOS

The Architecture of Business Intent with Data Products

How Semantic Metric Trees Improve Data Product ROI

Why AI Costs More Than It Should

Building Unified Semantics for Data Quality Management in Manufacturing

Why Cheaper AI Tokens Are Increasing Enterprise AI Costs

Making Data Easier for AI to Understand

Why AI gets it wrong and how data products fix that

The Modern Data Company and Leidos Partner to Organize Fragmented Federal Data Into Actionable Insights

Context Native: The Data Product Foundation AI Agents Need

Adding the Missing Layer: How Banks Are Activating the Data Stack They Already Built

Context is the New Currency: How Understanding Your Data Unlocks AI-Readiness

2026 Report Uncovers What's Holding Back Enterprise AI and Decision-Making