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Graphs 101: Understanding Data Graphs and Knowledge Representation

Following our introduction to graph structures, let's dive deeper into data-only graphs—particularly knowledge graphs—which have revolutionized the way we model and connect information.Data Graphs: The Relationship RevolutionAt their core, data graphs rep...

Graphs 101: Understanding the Foundations of Graph-Based Systems

Graphs are everywhere—whether powering search engines, optimizing logistics, or driving AI decision-making. Yet, despite their widespread use, the term "graph" is often used interchangeably across domains, leading to confusion.To cut through the noise, le...

Navigating Data Chaos: Turning the Compass of Confusion into a Business-Driven AI Framework

Data management often feels like a compass spinning without true North—different teams pulling in opposite directions, governance operating in a vacuum, and customer needs frequently overlooked.To address this, I’ve reimagined the Compass of Confusion—a m...

From Data to Ontology: How Data Object Graphs Accelerate Knowledge Engineering

The intersection of Data Object Graphs (DOGs) and Knowledge Graphs (KGs)/Ontologies is sparking a lot of discussion. While Knowledge Graphs are excellent at representing structured relationships, DOGs introduce a dynamic, executable process that accelerat...

Data Object Graphs vs. Knowledge Graphs: What’s the Difference?

A common question we get is: How do Data Object Graphs (DOGs) differ from traditional Knowledge Graphs (KGs)? While both leverage graph structures, their core purpose, structure, and functionality are fundamentally different.In short:📌 Knowledge Graphs r...

AI Agents & Data Object Graphs: The Future of Business Process Querying

In the world of business process automation, AI-driven decision-making, and real-time data interactions, traditional homogenized data models and centralized graph approaches fall short. Businesses need a way to query, navigate, and interact with processes...

Beyond Centralized Data: Process-Driven Data Modeling with Data Object Graphs (DOGs)

For years, organizations have been trying to modernize data architectures with distributed approaches like Data Mesh—only to end up reverting back to centralized models like 3NF, Star Schemas, or Data Vaults. Why? Because the missing piece has always been...

AI Digital Twins: Fixing the 8 Biggest Digital Transformation Failures

Digital transformation has been a buzzword for over a decade, yet the failure rate remains shockingly high. Organizations continue to struggle with execution, even after millions in investment.Why? Because transformation isn’t just about tech—it’s about p...

Critical Success Factors for AI-Driven Transformation: Lessons from the Field

After years of leading AI transformation initiatives, one truth stands out: successful AI adoption isn’t just about technology—it’s about business transformation, culture, and execution.Many organizations sink millions into AI, only to see projects stall ...

AI Business Twins: 4X Faster Business Transformation with AI Digital Twins 🚀

Just as engineers simulate bridges and aircraft designs before building, AI now enables businesses to simulate transformation before implementation.With AI-powered Digital Twins, we can eliminate much of the guesswork in business transformation—accelerati...

Data Mesh Isn’t Dead—It’s Just Gone AI-Native

The Data Mesh revolutionized how we think about data products, but in the age of AI, it needs to go further.While Data Mesh solved key data-sharing challenges, it never fully addressed: 1️⃣ End-to-end business use case delivery (including governance) 2️⃣ ...

From Miner to Designer: How AI is Redefining Idea-to-Prototype Acceleration

Just had a great discussion with Eddie Short on how GenAI is revolutionizing the journey from idea to industrial prototype—with real UX and business functionality in front of the customer faster than ever before.The emergence of Large Language Models (LLM...

Changing AI Wheels Without Stopping the Car: How to Build a Continuous AI Adoption Engine

AI implementation challenges are surfacing everywhere—companies sinking millions and spending years trying to get AI to work, only to struggle with adoption.After years of deploying AI across industries, we’ve learned a fundamental truth:🚨 AI projects wi...

AI Breeds a Better DOG: Automating Business Process Execution with AI-Generated Data Object Graphs

We’re taking AI-powered automation to the next level—AI-generated Data Object Graphs (DOGs) as AI Digital Twins.The challenge? Bridging the gap between process design and execution.Most businesses still rely on static, manually crafted workflows, making i...

The Disappearing Divide: Merging Operational and Analytical AI in Real-Time

Whoooaaa! We’ve just hit a major milestone.For years, the gap between operational (transactional) systems and analytical (decision-making) systems has been a major challenge. But that divide is vanishing—right now!Using our Data Product Pyramid GenAI tool...

Separating Knowledge from Processing: The Key to Scalable Data Products

A few years ago, I built an Apache Spark-based analytics engine for a major financial institution. It was supposed to be the ultimate solution—one engine to rule them all, capable of handling every use case.But reality hit fast. The first use case we tack...

Rethinking Data Quality in the Age of AI Data Products

There's a lot of talk about getting data “in order” before doing AI, including traditional Data Quality (DQ) initiatives. But from our experiences delivering AI-driven Data Products, we need a fundamental shift in how we think about Data Quality in the AI...

Top-Down or Bottom-Up?

What's the Right Approach to Data Products?Which approach delivers the most value when building data products?🔼 Top-Down: Start with the business use case first. Define the problem before doing any data work. Once clear, find and package only the data yo...

Building Data Products That Matter: The Data Product Pyramid in Action

We are excited to be guiding another organization on their Data Product journey using our Data Product Pyramid process! 🚀Too often, data initiatives get bogged down in infrastructure, governance debates, or endless data modeling exercises before proving ...

Release the Greyhounds: From Prompt to Business Process with AI Digital Twins

I had a fantastic session with Peter Everill diving into "Quantifying Your Value: The Framework Used to Realise £100m Profit" on Kyle Winterbottom’s Orbition Group podcast (link here).Peter laid out his consultancy-based framework for delivering end-to-en...

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