ANALYTICS INSIGHTS
Transform data into the best decisions
Recent Analytics Insights
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AI transforms insurance: See 8 examples of how it worksUsing AI in insurance can boost value for customers, insurance companies and stakeholders alike. Examples range from stronger fraud detection and improved customer service to optimized underwriting processes and competitive advantage. Learn more about how AI is transforming the industry.
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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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What is AI modeling?AI modeling involves creating programs that use one or a combination of algorithms to allow computers to think, learn and predict outcomes. Much like a human brain, AI models absorb input data – numbers, texts, images, video, sound – to learn how to predict outcomes or solve specific tasks without explicit instructions at every step.
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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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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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AI como fonte de ansiedade: Manter a calma perante as mudançasA AI como fonte de ansiedade não é uma brincadeira. Quer receie certos trabalhos tornarem-se obsoletos, distorção da informação, ou simplesmente deixar escapar oportunidades, compreender a AI como fonte de ansiedade será fundamental para ultrapassar esses sentimentos.
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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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Utilização de*** dados sintéticos para impulsionar avanços na AIAprenda porque é que os dados sintéticos são vitais para as iniciativas em AI, como os negócios os utilizam para desbloquear o crescimento, e como podem ajudar a fazer face aos desafios éticos.
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O que são alucinações de IA?Separar os factos da ficção gerada pela IA pode ser difícil. Fique a saber como é que os grandes modelos de linguagem conduzem a alucinações de IA – e descubra como usar a GenAI de forma responsável.
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O que são chatbots?Os chatbots são uma forma de IA conversacional desenhados para simplificar a interação humana com os computadores. Aprenda mais sobre os chatbots que são utilizados em negócios e como estes podem ser incorporados em aplicações 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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Impeça fraudes em aplicações de seguros!Os vigaristas adoram a facilidade com que conseguem cometer crimes nos canais digitais. As companhias de seguros inteligentes estão a utilizar dados desses canais (impressão digital do dispositivo, endereço IP, geolocalização, etc.) juntamente com análise e machine learning para detetar fraudes nas aplicações de seguros que são perpetuadas por agentes, clientes e grupos criminosos organizados.
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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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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.
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10 ways analytics can make your city smarter From child welfare to transportation, read 10 examples of analytics being used to solve problems or simplify tasks for government organizations.
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
Have you heard the one about the retailer that discovered diapers and beer are often purchased together? What about the telco that can predict your likelihood to switch carriers based on how many of your friends have already switched? These businesses used data mining to uncover completely unexpected insights in their data. What secrets are hiding in your ever-growing data stores? Find out with data mining.
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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