ANALYTICS INSIGHTS
Transform data into the best decisions
Recent Analytics Insights
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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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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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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.
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Analytics: A must-have tool for leading the fight on prescription and illicit drug addictionStates and MFCUs now have the analytics tools they need to change the trajectory of the opioid crisis by analyzing data and predicting trouble spots – whether in patients, prescribers, distributors or manufacturers. The OIG Toolkit with free SAS® programming code makes that possible.
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Detetar e prevenir a fraude nas aplicações bancáriasA fraude nos créditos, por norma, começa por uma candidatura falsa. É por isso que é tão importante usar a análise logo no ponto de partida. Aprenda como a análise e a aprendizagem automática podem detetar fraudes logo nos primeiros pontos de contacto dos pedidos ao reconhecer os maiores desafios – identidades sintéticas.
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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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SAS CIO: Porque é que os líderes devem cultivar a curiosidade em 2021Com a mudança que todos enfrentamos este ano, os CIOs devem contar com a curiosidade para desempenharem um papel crucial na forma como vamos conhecer os desafios que temos pela frente. Desde o momento em que o COVID-19 nos atingiu, a nossa empresa de TI confiou na curiosidade - esse forte desejo de explorar, aprender, saber - para alimentar as mudanças urgentes necessárias. E é a curiosidade que nos permitirá satisfazer as necessidades do futuro do trabalho pós-pandémico.
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Previsão da carga: Assegurar que a oferta satisfaz a procura de energiaA previsão da carga ajuda os fornecedores de energia a satisfazer a procura de clientes residenciais e empresariais. À medida que os recursos de energia renovável aumentam, torna-se crucial a necessidade de uma plataforma tecnológica que se adapte aos requisitos de previsão de carga.
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5 formas de aumentar solidez empresarial no futuroInnovation, agility and customer-centricity frequently top the list of companies’ strategic objectives, and now the most urgent priority is resilience. Given this new urgency, it’s worth taking a close look at the underpinnings of resilience and how they could be applied in any industry. This article explores how analytics can help boost resilience and includes key elements to keep your organization resilient.
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Resilience in the face of unpredictabilityUnpredictability can “shatter and reshape” a society. And in these unpredictable times, it is important to remain resilient and be prepared to bounce back. This article explores what it truly means to be resilient, how to build it, and how analytics can help you act when your resilience is tested.
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Homelessness data holds insights to a hidden problemSAS partnered with The Carying Place, an organization that supports working homeless families, to find new ways to measure indicators of participant success and provide families the help they deserve.
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Finding COVID-19 answers with data and analyticsLearn how data plays a role in optimizing hospital resources, understanding disease spread, supply chain forecasting and scientific discoveries.
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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