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La ciberseguridad en el sector de telecomunicaciones (TELCO) cobra especial urgencia en Centroamérica y el Caribe, en un contexto donde estas empresas figuran entre los sectores más atacados globalmente, señalan especialistas. Según datos de Kaspersky Managed Detection and Response, en el primer semestre de 2024, las empresas de telecomunicaciones sufrieron
Most analytical journeys start the same way – with a question. When did we have the highest profit? Which customers are driving growth? What segment should we look at next? In traditional analytic workflows, turning those questions into answers often requires navigating menus, configuring visuals, writing calculations and interpreting results
Shahrzad Azizzadeh and team discuss optimizing inspector assignments using SAS Optimization in federal and state meat processing facilities.
There’s a new reality. Managing, organizing and analyzing data alone is no longer enough. What really matters is how decisions are made, governed and executed. To be successful, enterprises need a unified approach that allows decisions to sit at the center, bringing people, systems and data together. While there are
Insurance is a business built on trust. Each policy represents a promise that insurers must be able to explain, defend and ultimately fulfill. When you add in AI becoming more embedded in underwriting, pricing, claims and customer engagement, that promise is being mediated by data and algorithms. An IDC report,
This is the last article in a series about the nonnegative matrix factorization (NMF). In this article, I run and visualize an NMF analysis of the Scotch whisky data and compare it to a principal component analysis (PCA). Previous articles in the series provide information about the whisky data, the
Agentic AI has been heralded as a top tool for efficiently orchestrating customer engagement activities at insurance companies. It can: Automate repeatable, rule-based processes that affect customer experience (think claims processing and customer onboarding). Rapidly retrieve disparate data, analyze risks and recommend decisions. Help lower operational costs while keeping humans
Advanced AI technology is transforming how governments think, work and solve problems. With new terminology and evolving tools, understanding AI can feel overwhelming. Before diving into new applications, it helps to build a strong foundation in its core concepts. This overview breaks down three of today’s most prominent AI capabilities: machine learning,
Optimice y modernice todo el proceso de planificación financiera con analítica El problema El ritmo de los cambios normativos, junto con el crecimiento explosivo de los datos financieros y operativos disponibles, ha hecho que las soluciones de contabilidad tradicionales sean incapaces de proporcionar la información crítica sobre los costes, la
If you have decided to track your food intake recently, you might feel overwhelmed by all the options. There are hundreds (even thousands) of food tracking apps available, with new ones popping up all the time. Apps like MyFitness Pal, Lose It! and Cronometer have been around for a long
Many conversations about AI agents focus on models and frameworks. But when organizations attempt to deploy agents in real operational environments, a different challenge quickly emerges. How agents reliably and securely access enterprise data. Without reliable access to relevant data, AI agents struggle to support operational decisions. Whether diagnosing equipment
Governance, risk and compliance (GRC) has evolved beyond a control mechanism or regulatory safeguard. In today’s environment, it forms the operational backbone of effective corporate management – enabling organizations to identify risks early, meet regulatory expectations reliably, and ensure that decisions and processes remain transparent and traceable. Yet many organizations still
Enterprise decisioning has moved far beyond isolated, one‑off decisions. Today’s organizations operate in environments where decisions are continuous, high‑volume and increasingly autonomous – executed thousands to millions of times per day across credit origination, fraud detection, next‑best action, pricing and personalized engagement. These decisions are not monolithic. They combine business
Everyone is racing to scale their AI right now, but we keep hitting the same uncomfortable truth: your AI platform is only as good as what you feed it. The problem? Real-world data is a mess. It’s hard to get your hands on. It's expensive to clean, often biased and
A nagging question remains after asking, “What’s next after zero-click search?” How do frontier models – like OpenAI’s o3 series or Google’s Gemini 3 – learn? Garbage in, garbage out Large language models (LLMs) learn from massive amounts of text data, including billions of words, public information, and, you guessed it,