
Resources
Collection of news, articles and features on all things data, from the infoboss team…
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Data compliance
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Part 4. Clean the data before you move it.
Successful cloud migration starts with data intelligence, not data movement.
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Part 3. Data foundations.
When data foundations work, they are rarely noticed. They simply allow the business to move faster, with confidence.
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How to achieve Santa-level precision with your data
Have you ever stopped to appreciate just how extraordinary Santa and his team of elves are at managing and exploiting data? In many ways, he’s the gold standard the rest of us are chasing. When you look closely at the scale of his operations – and the flawless service he delivers – the secrets behind…
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infoboss + Regulativ.ai collaborate…
infoboss & Regulativ.ai are creating an end to end, AI driven approach that helps organisations manage data confidently, streamline regulatory obligations and reduce the cost and complexity of compliance.
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The benefits of white labelling…
As AI and data management evolve, consultancies and service providers face a choice: invest heavily in developing technology, or leverage a proven platform and make it their own. White labelling a data management or RAG platform lets you strengthen your brand, expand your service portfolio, and unlock new recurring revenue – without the complexity of…
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Why do 95% of AI projects fail?
AI pioneers are focussing on the technology and not the benefits, of focussing on the outputs and not considering the inputs. Implementing AI will undoubtedly herald a new dawn in business benefit realisation BUT and it’s a big BUT, only if the organisation sorts out its data management processes once and for all. So in…
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Why no-code data governance matters
By lowering the barriers, infoboss AI makes governance something that everyone can see, understand, and take part in. Executives can understand rules at a glance, compliance officers can own them directly, and IT teams are freed to focus on higher-value projects.
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What is AI Data Preparation?
In the rush to adopt artificial intelligence (AI) and automation, one critical step is often overlooked: data preparation. Without high-quality, well-structured data, even the most sophisticated AI models or analytics platforms will fail to deliver reliable results. AI data prep (artificial intelligence data preparation) is the process of collecting, cleaning, organising, and structuring raw data…


