Sherlock Holmes Mode: Getting to Know Your Data
In Part 2, we discussed the importance of labelling your data to create a ground truth. Now that we have our dataset, the temptation is to immediately start “fixing” it.
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The Ground Truth: Strategies for High-Quality Data Labeling
In Part 1, we discussed why data preparation is the bedrock of Machine Learning. Now, we enter the most critical phase of that preparation: Creating the Ground Truth.
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Garbage In, Garbage Out: Why Data Prep is the Real Work of Machine Learning
There is a romanticised version of Machine Learning (ML) that exists in movies and marketing pitch decks. In this version, the hard work is the “AI” itself, complex neural networks, cutting-edge algorithms, and futuristic code.
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10 Tech Predictions for 2026: The Year of the "Agentic" Enterprise Author
2025 was a year of friction for the entire tech industry. We saw the “AI Boom” collide with the reality of legacy infrastructure, creating a gap between expectation and delivery.
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Why 17th-Century Secretary Script Is So Difficult
Some projects are technical. Some are operational. And every now and then, one is quietly profound.
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When Data Becomes Art
How We See the World: London has a new landmark, and for once it’s not another glazed tower, street installation or temporary sculpture that people take selfies with for a week and forget.
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Spreadsheets as Spectacle: Meet Excel Esports
It sounds ridiculous. Fifteen people hunched over laptops. The screens glow. Fingers fly across keys like speedy dance moves.
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A New Chapter in Data Engineering
High Digital has officially kicked off a new data warehouse implementation that redefines how modern analytics environments are designed
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Agentic AI for Enterprise will Reshape Digital Operations
Let’s be blunt: most organisations are still treating AI like a glorified intern, useful, clever, occasionally dazzling, but never fully trusted to run the show.
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