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Edge computingWith traditional methods, data is captured, stored and analyzed later – limiting how quickly businesses can act on insights from the data. With edge computing, IoT data is processed at the edge of a network – right where it’s created or collected – avoiding delays and enabling real-time processing and action.
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How AI and advanced analytics are impacting the financial services industryTop SAS experts weigh in on the topics that are keeping institutions up at night and fraudsters in a job.
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AI in banking: Survey reveals factors for successWhat do banking executives report about their experiences with AI? Where are they focusing today? What’s working? What are their plans for the future?
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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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IoT: The customer experience accelerator you can't afford to ignoreIoT represents a powerful source of data that, when combined with analytics, can yield insights on everything from behavior to emotions to health. And that's why it's key to improving customer experience.
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Data lineage: Making artificial intelligence smarterFor AI to reach its full potential, the data feeding its algorithms and models needs to be well-understood. Data lineage plays a vital role in understanding data, making it a foundational principle of AI.
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How to drill a better hole with analyticsFrom drilling holes to preventing health care fraud, learn about some of the new technologies SAS has patented with IoT and machine learning technologies.
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IFRS 17: Waiting is not an optionIFRS 17 is a principles-based accounting standard for the future-oriented valuation of insurance contracts. Designed to increase financial transparency, IFRS 17 requires insurers to report in more detail on how insurance and reinsurance contracts affect their finances and risk.
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IT/OT convergence: The dilemma of the IoT perception gapThe IoT phenomenon demands intimate collaboration between information technology (IT) and operational technology (OT). But IT and OT have distinct gaps in perception about the goals and outcomes of IoT initiatives. Tom Bradicich explains why IT/OT convergence is essential for successful IoT projects.
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Five AI TechnologiesDo you know the difference between artificial intelligence and machine learning? And can you explain why computer vision is an AI technology? Find out in this short explainer.
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IoT in healthcare: Unlocking true, value-based careGiven the potential of IoT – and the challenges of already overburdened healthcare systems around the world – we can’t afford not to integrate IoT in healthcare.
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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 considering these ten questions as a preliminary guide.
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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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A guide to machine learning algorithms and their applicationsDo you know the difference between supervised and unsupervised learning? How about the difference between decision trees and forests? Or when to use a support vector algorithm? Get all the answers here.
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The analytical CRO and the risk aware CFOTo create a more risk-aware organization, the most important collaborative relationship for the CRO is with the CFO and the finance team. The CFO and CRO – as the executives responsible for budgeting and supervision – tend to get caught in the middle of competing objectives.
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Big data in educationA recent MIT Sloan Management report highlights how businesses are using analytics as a source of innovation -- so are universities, says SAS' Georgia Mariani.
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Effective real-time marketingEffective real-time marketing is about engaging with customers whenever and wherever they are in their buying journey. Organizations should also be focused on knowing what the customer wants (product, pricing, experience, etc.) based on real-time analytics and predictive modeling.
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Machine learning and artificial intelligence in a brave new worldWhat is the interplay between man and machine in a brave new world with AI?
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3 steps for AI ethicsWill artificial intelligence benefit humanity or usher in a series of unintended consequences? AI ethics may be one way to ensure artificial intelligence is used for good.
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Nerd in the herd: protecting elephants with data scienceA passionate SAS data scientist uses machine learning to detect tuberculosis in elephants. Find out how her research can help prevent the spread of the disease.
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What do drones, AI and proactive policing have in common?Law enforcement and public safety agencies must wrangle diverse data sets to be effective in their operations. Intelligence analysts are using that data to apply machine learning and AI for more proactive policing.
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Meet the data scientist: Kristin CarneyWhen Kristin Carney graduated with a BS in mathematics, she wasn't sure what she wanted to do with her degree. That’s when she began researching data science.
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Meet the data scientist: Daymond LingDaymond Ling believes the right personal traits are more important than technical skills when it comes to being a successful data scientist.
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Meet the data scientist: Colin NugterenData scientist and CAO Colin Nugteren says while every day is different, one thing remains the same. He ends each day with SAS® Visual Analytics.
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Using data to change the worldApplying data science for social good has led to new and creative ways to address issues related to education, poverty, health, human rights, the environment and more.
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How to improve your AI marketing skillsMarketing teams can use current AI capabilities to enhance their efforts around campaign automation, dynamic pricing based on forecasting models, and by providing more relevant, real-time customer offers.
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AI marketing: What does the future hold?AI marketing uses artificial intelligence and analytics to improve marketing results while enhancing customer experiences through real-time personalization.
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Connected vehicles: IoT steers a new direction for OEMsWith IoT and analytics, automakers and their partners can reshape business models, find new ways to monetize data and serve customers better.
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IoT challenges in the connected supply chainThe IoT Is set to revolutionize supply chain management, but there are certain challenges it must overcome first. Here’s what you need to know.
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Fraud detection and machine learning: What you need to knowFrom integrating throughout operations to maintaining customer service, machine learning – supervised and unsupervised – is a critical part of the fraud detection toolkit. Here’s what you’ll need to consider to get started.
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Demand forecasting and the 7 habits of effective retailersWhy do some retailers consistently outperform others? Retail Systems Research reveals some key reasons and offers essential advice for those who want to become (or continue to be) winners.
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Proactive detection – A new approach to counter terrorTo counter terror, investigative teams can better utilize the data they already have by applying a fresh approach with these steps to proactive detection.
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