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Articles mentioning Twentynext
Without proper management, your business-critical data environment deteriorates faster than you think
A live data environment without solid service and management quickly becomes less reliable: models drift, pipelines fail, and dashboards start showing outdated numbers. This article explains why reactive support falls short, which four pillars keep business-critical environments stable, and how ISO-certified processes make the difference between an AI initiative that keeps delivering value and one that slowly fades away.
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Without proper management, your business-critical data environment deteriorates faster than you think
A live data environment without solid service and management quickly becomes less reliable: models drift, pipelines fail, and dashboards start showing outdated numbers. This article explains why reactive support falls short, which four pillars keep business-critical environments stable, and how ISO-certified processes make the difference between an AI initiative that keeps delivering value and one that slowly fades away.
Mentioned as Twentynext
Data maturity assessment: which of the 5 stages is your organization in?
A data maturity assessment shows where an organization stands across five maturity stages, from ad hoc to fully transformative. This article breaks down each stage with practical scoring criteria, a real-world scenario, and clear next steps to help you move forward.
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Why Strong Data Engineering Makes Your AI Project Scalable
Many AI projects perform brilliantly in a test environment, only to break down once they go live. The root cause is rarely the model itself. More often, it’s the data foundation underneath it. This article explains what data engineering actually involves, why it’s the critical success factor behind scalable AI, and how Twentynext puts it into practice.
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Choosing a BI Platform? 7 Pitfalls for Growing Companies
For growing companies, choosing a Business Intelligence platform isn’t just a technical decision, it’s a strategic one. Yet many BI initiatives fail for the same seven reasons, and most of those issues only become visible later. This article breaks them down and shows you how to avoid them.
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An R&D Week at Twentynext: From Research Paper to Production Code
At Twentynext, data scientists don’t sit idle between projects. They read research papers, build prototypes, and sometimes turn them into production code within the same week. This article shows what that R&D cycle looks like in practice—and why it matters for both clients and talent.
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When Is Your Organization Truly Ready for an AI Use Case?
Many organizations want to adopt AI but lack the foundations to do it responsibly. This article walks through a step-by-step approach to assess whether your organization is ready for an AI use case, from data quality and business fit to governance and scalability.
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What CRISP-DM Brings to Modern Data Science Projects
CRISP-DM has been the go-to methodology for data science projects for decades. But what does it actually add now that more organizations want to roll out generative AI? This article shows how a structured approach makes the difference between a model that performs well in a lab and an AI solution that delivers real business value.
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