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May 30, 2026

12 AI Automation Examples That Deliver Value

Most AI projects stall because use cases sound impressive in workshops but never map cleanly to business processes. This article walks through 12 automation examples — from document processing to executive reporting — that reduce delay, remove repetitive work and improve decision quality where data foundations allow it.

May 26, 2026

What Is Google Cloud Platform Used For?

Google Cloud Platform is a collection of cloud services that help organisations run applications, store and process data, build analytics workflows, improve security, and put AI into production. For small and mid-sized businesses, the real value is not simply moving servers into the cloud but creating an operating model where data is easier to manage, teams can work faster, and systems can scale without constant rework.

May 25, 2026

What Google Cloud Data Platform Architecture Should Actually Solve

Most data platforms fail not because cloud tools are weak, but because architecture was treated as a product checklist rather than an operating model. A sound Google Cloud data platform must support analytics, operational decision-making, and AI use cases without becoming expensive or chaotic.

May 25, 2026

Hyperscale AI Architecture: Why Data Center Connectivity Is the New Competitive Moat

The AI infrastructure race has a hidden bottleneck that most enterprises are just starting to understand: it's not GPUs or power, it's the network fabric connecting them. Here's why data center connectivity is becoming the decisive factor in who wins the AI race.

May 25, 2026

AI Services Sovereignty: The True Cost of Every Hosting Model

When AI services touch sensitive data, where they run matters as much as what they run. We break down the sovereignty premium embedded in every hosting model—from bare metal to public APIs—and show what it actually costs as a percentage of your project budget.

May 20, 2026

Embodied AI: From Table-Tennis Robots to Factory Floors

Exploring the shift from chatbots to physical AI systems that perceive, act, and learn in the real world—humanoid robots, industrial automation, and the integration of AI into tangible hardware.

May 18, 2026

The Pivot to 'Agentic AI' & Usage-Based Pricing

GitHub's shift to usage-based pricing for Copilot and the blocked Meta Manus acquisition signal a pivotal move from chatbots to autonomous AI agents. This article explores the implications of agentic AI, the economic pressures driving usage-based models, and what it means for enterprises adopting AI at scale.

April 28, 2026

AI Agents and Autonomous Workflows: The Next Evolution Beyond Chatbots

AI agents are moving beyond simple chatbots to execute complex, multi-step workflows autonomously. This article explores the shift, real-world applications, challenges, and what it means for businesses.

April 20, 2026

Common Architectural Patterns in the Age of AI

As AI becomes the default compute paradigm, architectural patterns are shifting. This post explores key AI-first patterns like Orchestrator-Worker, RAG Pipeline, Feedback Loops, and Multi-Modal Fusion.

March 27, 2026

Vertex AI in Production: The 5 'Gotchas' You Need to Watch For

Moving from a notebook to production on Google Cloud's Vertex AI is rarely a straight line. Here are the five key architectural and operational moments where things usually break, and how to stay ahead of them.

March 23, 2026

The Rise of Autonomous Research and Coding Agents

AI agents are transitioning from simple chat interfaces to deep research and autonomous coding systems. This shift is redefining how we build software and analyze markets, turning AI from a passive assistant into a proactive partner.

March 20, 2026

Physical AI: Agents Beyond the Screen

The next frontier of agentic AI isn't in your browser—it's in the real world. Exploring the transition from LLMs to Physical AI.

March 18, 2026

AI Governance: Why the DAMA Principles are More Relevant Than Ever

How the established DAMA Data Management Principles provide the essential foundation for governing the next generation of AI agents.

March 16, 2026

The Microservices Moment of AI: Multi-Agent Orchestration

Why the future of AI isn't one giant model, but coordinated squads of specialized agents working together.

March 13, 2026

The 5 Layers of AI they discussed in Davos

A concise summary of the 5 layers of the AI ecosystem (Compute, Models, Fine-Tuning, Agents, Applications) as discussed by tech leaders at the World Economic Forum.

March 11, 2026

The End of the 'Data Engineer'? The Evolution to AI Engineer

As AI agents replace static dashboards, the traditional 'Data Engineer' is rapidly evolving into an 'AI Engineer'. Are we witnessing the end of an era, or just a major rebrand?

March 9, 2026

The Mandate for 'AI-Ready' Data Foundations and Governance

The tech industry has hit a hard realization in 2026: AI is only as good as the first-party data powering it. Fix your foundation, or your LLMs will stay in the toy box.

March 2, 2026

The Shift to Agentic AI and Autonomous Workflows

We are seeing a massive transition from simple, conversational AI pilots to full-scale agentic workflows in production. This isn't just an evolution; it's a paradigm shift in how enterprises leverage artificial intelligence. The days of siloed chatbots handling basic queries are rapidly giving way to sophisticated, autonomous agents capable of complex, multi-step tasks.

February 20, 2026

Data Mesh Governance: How to Enforce Policies Without Becoming a Bottleneck

Data mesh promises decentralized ownership, but often delivers decentralized chaos. The fix isn't more meetings—it's automated, federated governance that acts as a guardrail, not a gatekeeper.

February 18, 2026

SQL vs. NoSQL in 2026: The Pendulum Swings Back

The 'NoSQL by default' era is over. With Postgres becoming a universal database and NewSQL solving the scaling problem, relational is cool again.

February 16, 2026

Technical Debt as an Asset: When Ugly Code is a Strategic Advantage

Perfection is the enemy of done. We explore why startups should treat technical debt like a financial loan—leverage it for speed, but have a plan to pay it back.

February 13, 2026

The 'Data Product' Fallacy: Wrapping Garbage in a Gift Box

Calling a table a 'product' doesn't make it valuable. We explore why the Data Mesh hype is failing where it matters most: data quality and usability.

February 11, 2026

AI and the Market Sentiment: From Hype to Reality

The initial gold rush is cooling, but the real work is just beginning. We examine how market sentiment towards AI is shifting from blind optimism to pragmatic scrutiny.

September 4, 2025

On Data Management

As a Data Professional with over two decades in the trenches of enterprise data, I can tell you that the current excitement around AI, while invigorating, is putting immense pressure on the very foundations of our work.

August 15, 2025

The Visionary Data Architecture

For too long, we've been designing data systems as passive repositories. A warehouse. A lake. These are static, historical metaphors. We need to stop building data museums ...

July 4, 2025

From Big Data To ...

For the last decade, the big story in data was 'Big Data' — the V's: Volume, Velocity, and Variety. It was a story about infrastructure,...

January 20, 2025

Navigating the Data Frontier

A Senior Strategist's Guide to Enterprise Data Management Assessment

April 28, 2018

Digitalisation Simplicity

There are two dimensions that matter most to the people...