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Shrinking budgets, rising citizen expectations and increasingly sophisticated fraud schemes have stretched resources thin. Meanwhile, outdated systems and manual processes make it harder for frontline workers to keep pace. According to a global study commissioned by SAS, a striking 85% of policymakers and public sector leaders cite the fight against
Fraud remains a huge challenge for governments and inspectors at all levels, as fraudsters today are more successful than ever. Technologies such as analytics and AI have tremendous potential to support investigations. Why are fraudsters so successful these days? Partly because they seek easy targets, work hard to stay off
Los valores perdidos —también llamados missings— son ese invitado inesperado (y a veces incómodo) que siempre aparece en tu dataset. Aunque muchos los ven como un simple estorbo, la forma en que los manejes puede marcar la diferencia entre un análisis sólido y conclusiones engañosas. En esta entrada revisaremos: Las
Think of data engineering as plumbing for the digital world. All those smart dashboards, AI models and analytics reports don’t work unless someone builds the pipelines that bring clean, usable data to them. That someone is a data engineer. Why data engineers are suddenly in the spotlight AI is everywhere today
Machine learning engineers are among the most sought-after professionals in the data analytics and AI space today. But behind the buzzwords and job titles lies a role that requires data literacy and a range of skills in statistics, software deployment, critical thinking and ethical judgement. If you're wondering what this
If you have a background in pharmacy, life sciences, biotechnology, or statistics – and you’re curious about the world of clinical research – there’s one career path you might want to explore: clinical SAS programming. Maybe you’ve heard the term before and wondered what it really involves. The good news?