ANALYTICS INSIGHTS
Transform data into the best decisions
Recent Analytics Insights
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AI and humanity: Collaborating to solve global problemsDisplaced communities, the food crisis and natural disasters – these situations affect quality of life, and even the ability to survive. Could artificial intelligence be the unexpected boost humanity needs? Could it accelerate our ability to make a positive, lasting impact? Learn more and read examples of how AI is being used to find solutions to global problems.
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Five AI technologiesDo you know the difference between artificial intelligence and machine learning? Can you explain the basics of AI technologies like GenAI and AI agents? Read our overview to understand these and other technologies behind the AI craze.
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La IA transforma los seguros: ocho ejemplos de su funcionamientoEl uso de IA en seguros puede aumentar el valor para los clientes, las compañías de seguros y las partes interesadas por igual. Los ejemplos van desde una detección de fraude más fuerte y un servicio al cliente mejorado hasta procesos de suscripción optimizados y ventajas competitivas. Descubre más información sobre cómo la IA está transformando la industria.
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¿Qué son los modelos de IA?La modelización de IA implica la creación de programas que utilizan un algoritmo o una combinación de algoritmos para permitir a los ordenadores pensar, aprender y predecir resultados. Al igual que el cerebro humano, los modelos de IA absorben datos de entrada —números, textos, imágenes, vídeo, sonido— para aprender a predecir resultados o resolver tareas específicas sin instrucciones explícitas en cada paso.
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Understanding digital twin technologyLearn how digital twin technology can change industries from health care to manufacturing, and shape the future of data modeling and process improvements.
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Big data in government: How data and analytics power public programsBig data in government is vital when analyzed and used to improve the outcomes of both public and private sector programs – from emergency response to workforce effectiveness. The vast volumes of data created every day are the foundation of insightful changes for government agencies across the globe.
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Unlocking a strategic approach to data and AIAI is only as good as the data that powers it – this is a fundamental truth about data and AI that defines the limits of what’s possible with artificial intelligence. It may seem surprising, but it's rarely a bad algorithm or a bad learning model that causes AI failures. It's not the math or the science. More often, it's the quality of the data being used to answer the question.
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Ansiedad frente a la IA: mantener la calma ante el cambioLa ansiedad frente a la IA no es ninguna broma.— Tanto si temes que tu trabajo se quede obsoleto, que la información se distorsione o simplemente perderte algo, comprender la ansiedad que provoca la IA puede ayudarte a vencerla.
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Fraud detection and machine learning: What you need to knowMachine learning and fraud analytics are critical components of a fraud detection toolkit. Discover what you’ll need to get started defending against fraud – from integrating supervised and unsupervised machine learning in operations to maintaining customer service.
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Datos sintéticos para impulsar avances de IADescubre por qué los datos sintéticos son vitales para las iniciativas de IA, cómo los utilizan las empresas para desbloquear el crecimiento y cómo pueden ayudar a abordar los retos éticos.
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¿Qué son las alucinaciones de IA?Separar la realidad de la ficción generada por la IA puede ser difícil. Aprende cómo los grandes modelos lingüísticos pueden fallar y conducir a alucinaciones de IA y descubre cómo utilizar la GenAI de forma responsable.
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¿Qué son los chatbots?Los chatbots son una forma de IA conversacional diseñada para simplificar la interacción humana con las computadoras. Aprende cómo se utilizan los chatbots en las empresas, cómo pueden incorporarse a las aplicaciones analíticas
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Next generation anti-money laundering: robotics, semantic analysis and AIAdding AI and machine learning to your anti-money laundering program can combat rising compliance pressures, complexity and risks. Learn about the results innovative financial institutions around the globe are getting from next-generation AML.
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A data scientist’s views on data literacyData literacy is a social imperative – and understanding data and data analysis is critical for being a responsible citizen. Get a data scientist and teacher's perspective on the value of having foundational knowledge so you can more easily tell data facts from data fiction.
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Shut the front door on insurance application fraud!Fraudsters love the ease of plying their trade over digital channels. Smart insurance companies are using data from those channels (device fingerprint, IP address, geolocation, etc.) coupled with analytics and machine learning to detect insurance application fraud perpetrated by agents, customers and fraud rings.
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4 strategies that will change your approach to fraud detectionAs fraudulent activity grows and fighting fraud becomes more costly, financial institutions are turning to anti-fraud technology to build better arsenals for fraud detection. Discover four ways to improve your organization's risk posture.
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Public health infrastructure desperately needs modernizationPublic health agencies must flex to longitudinal health crises and acute emergencies – from natural disasters like hurricanes to events like a pandemic. To be prepared, public health infrastructure must be modernized to support connectivity, real-time data exchanges, analytics and visualization.
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Analytics leads to lifesaving cancer therapiesA long-shot treatment offers hope to 10-year-old Harrison after he learns the DNA profile of his cancer is resistant to chemo. Find out how data and analytics play a role in cancer research and cancer treatments that are saving lives.
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Key questions to kick off your data analytics projectsThere’s no single blueprint for starting a data analytics project. Technology expert Phil Simon suggests these 10 questions as a guide.
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Analytics tackles the scourge of human traffickingVictims of human trafficking are all around us. From forced labor to sex work, modern-day slavery thrives in the shadows. Learn why organizations are turning to AI and big data analytics to unveil these crimes and change future trajectories.
Analytics: The Basics
- Overview
- Big Data Analytics
- Data Mining
- Predictive Analytics
- Statistical Analysis
- Blockchain
- Neural Networks
- Data Science
- Algorithm
Analytics
If you're reading this, you probably know at least a little – maybe even a lot – about analytics. According to Wikipedia, analytics is "the discovery and communication of meaningful patterns in data." Seems obvious, right? Where the real story with analytics lies, however, is in what you can do with it. Think in terms of possibilities. Opportunities. Discoveries. Made possible by technological advancements in analytics that were never even dreamed of not so very long ago, within your lifetime. So let's explore the topic of analytics together. We'll share insights from the brightest minds in analytics – insights that you can turn into ... well, it's up to you.
Big Data Analytics
As data floods your organization on a daily basis, the question is no longer "What is big data?" Instead, it's "What can we do with the big data we have?" The answer, of course, is integral to the future of your business. And big data analytics opens up the world of the possible. With big data analytics, you can implement data mining, predictive analytics, text mining, forecasting and optimization to explore your options and make the best possible business decisions.
Data Mining
¿Ha oído hablar del comerciante detallista que descubrió que frecuentemente se compran pañales y cerveza al mismo tiempo? ¿Qué hay de la empresa de telecomunicaciones que puede predecir su probabilidad de cambiar de operador con base en cuántos de sus amigos ya se han cambiado? Estas empresas utilizaron la minería de datos para descubrir información completamente inesperada en sus datos. ¿Qué secretos se ocultan en sus almacenes de datos en eterno crecimiento? Averígüelo con la minería de datos
Predictive Analytics
So you’ve embraced the power of collecting and analyzing data. That’s a great first step, but it just scratches the surface. To get the most out of your data, you need to anticipate the future, not just analyze the past.
Whether you want to attract new customers, assess payment risk, identify fraud or forecast energy demand, predictive analytics can provide answers to your most complex questions.
Statistical Analysis
Statistical analysis isn’t just for sports geeks and political pollsters. Every day, statistics plays a critical role in informing public policy and improving human welfare. The field of statistics has grown from sampling populations to analyzing even the biggest of big data sources.
Today’s statisticians are tracking endangered species, improving agricultural processes and predicting the best treatments for complex diseases. There's a lot going on with this influential field and the statistical programming techniques used by today’s statisticians.
Blockchain
What can you store in blockchain besides Bitcoin transactions? Insurance claims, medical records and even voting records can all be stored in blockchain. Simply put, blockchain is a distributed data architecture that stores data and transactions – and validates the accuracy of those transactions by consensus. Learn more about blockchain and how you can analyze blockchain data.
Neural Networks
Neural networks are computer programs designed to imitate how the human brain learns and searches for patterns. Often referred to as artificial neural networks (ANNs), they are ideally suited to solving real-world problems in different fields. Much like a human brain, they can be trained over time to improve their interpretations of data.
Data Science
Data science is a multidisciplinary field that broadly describes the use of data to generate insight. Unlike more specialized data-related fields, such as data mining or data engineering, data science encompasses the complete life cycle of translating raw data into usable information and applying it for productive ends in a wide variety of applications.
Algorithm
An algorithm is a list of step-by-step instructions designed to accomplish a specific task or solve a specific problem. When you think about it this way, algorithms are pervasive. A French onion soup recipe, for example, is an algorithm. Combine these inputs to generate an output. Algorithms basically work the same way with computers. Whether they’re converting binary numbers into letters so you can read what’s on your tablet screen or recommending stocks based on your risk tolerance, algorithms are fundamental in modern computing. This page will focus on computer algorithms.
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