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What is synthetic data? And how can you use it to fuel AI breakthroughs?There's no shortage of data in today's world, but it can be difficult, slow and costly to access sufficient high-quality data that’s suitable for training AI models. Learn why synthetic data is so vital for data-hungry AI initiatives, how businesses can use it to unlock growth, and how it can help address ethical challenges.
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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 anxiety: Calm in the face of changeAI anxiety is no joke. Whether you fear jobs becoming obsolete, information being distorted or simply missing out, understanding AI anxiety can help you conquer it.
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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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What are AI hallucinations?Separating fact from AI-generated fiction can be hard. Learn how large language models can fail and lead to AI hallucinations – and discover how to use GenAI responsibly.
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What are chatbots?Chatbots are a form of conversational AI designed to simplify human interaction with computers. Learn how chatbots are used in business and how they can be incorporated into analytics applications.
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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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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.
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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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Viking transforms its analytics strategy using SAS® Viya® on AzureViking is going all-in on cloud-based analytics to stay competitive and meet customer needs. The retailer's digital transformation are designed to optimize processes and boost customer loyalty and revenue across channels.
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Detect and prevent banking application fraudCredit fraud often starts with a falsified application. That’s why it’s important to use analytics starting at the entrance point. Learn how analytics and machine learning can detect fraud at the point of application by recognizing the biggest challenge – synthetic identities.
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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: Why leaders must cultivate curiosity in 2021With the change we’re all facing this year, CIOs should be counting on curiosity to play a crucial role in how we’re going to meet the challenges that lie ahead. From the moment COVID-19 hit, our IT organization has relied on curiosity – that strong desire to explore, learn, know - to fuel the urgent changes required. And it’s curiosity that will enable us to meet the needs of the future of work post-pandemic.
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Load forecasting: Ensuring supply meets energy demandLoad forecasting helps energy suppliers meet demand for residential and commercial customers. As renewable energy resources increase, the necessity for a technology platform that adapts to load forecasting requirements becomes crucial.
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Five ways your organization can enhance resilience for years to comeInnovation, 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.
Dataanalys: Introduktion
Om du läser det här så är du lite, eller till och med mycket kunnig inom dataanalys. Enligt Wikipedia är analys “upptäckten av mönster i data som kommuniceras på ett begripligt sätt.” Rätt så självklart, eller hur? Men den stora frågan inom dataanalys är hur den kan användas. Tänk möjligheter. Upptäckter. Allt det där som nu är möjligt med dataanalys, på grund av alla teknologiska framsteg, som vi tidigare inte ens vågade drömma om. Låt oss utforska dataanalys tillsammans. Vi delar med oss av insikter från ledande experter inom området - insikter som du kan omvandla till… ja, det bestämmer du själv.
- Välj ämne
- Big data analytics
- Datautvinning
- Prediktiv analys
- Statistisk analys
- Blockkedja
- Neurala nätverk
- 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.
Vad är datautvinning?
Har du hört talas om återförsäljaren som upptäckte att öl och blöjor ofta köps samtidigt? Eller om telekombolaget som lärde sig att förutse när du vill byta operatör, baserat på hur många av dina vänner som redan bytt? Dessa företag använde datautvinning för att få nya och helt oväntade insikter om sin affär. Vilka hemligheter döljer sig i ditt berg av data, som växer varje dag? Det får du reda på med datautvinning.
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.
Vad är neurala nätverk?
Neurala nätverk är datorprogram som utvecklats för att imitera hur människans hjärna lär sig och söker efter mönster. De kallas ofta artificiella neurala nätverk (ANN) och används främst för att lösa aktuella problem inom olika områden. Precis som en människas hjärna kan ANN tränas till att bli bättre på att tolka 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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