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Recent Analytics Insights
- AI in manufacturing: New oppportunities for IT and operationsAn AI survey reveals that leaders and early adopters in AI are making important advances and are identifying and expanding on what works as they use AI in more ways and more parts of their organizations.
- The Humanity in Artificial IntelligenceCould artificial intelligence be the change agent we need to solve many problems around the globe? Read how AI could accelerate our ability to have a a positive, lasting impact.
- 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.
- 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?
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Detect and prevent banking application fraudSince credit fraud often starts with a falsified application, it makes sense to have analytics-driven tools in place to detect fraud from the earliest point and across the life of the account.
- 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.
- Machine learning, Michael J. Fox and finding a cure for Parkinson’sUsing machine learning, data scientists developed a model that can help doctors accurately predict Parkinson's disease progression and start treatment earlier, when it will have greater impact.
- GDPR and AI: Friends, foes or something in between?The GDPR may not be best buddies with artificial intelligence – but GDPR and AI aren't enemies, either. Kalliopi Spyridaki explains the tricky relationship between the two.
- Seven tips for creating a self-service BI governance strategySelf-service BI and IT governance – sometimes the two seem at odds. Can they coexist peacefully? Live happily ever after? TDWI thinks so. They offer seven tips for creating a strategy that works for both.
- 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.
- Big data in government: How data and analytics power public programsBig data generated by government and private sources coupled with analytics has become a crucial component for a lot of public-sector work. Why? Because using analytics can improve outcomes of public programs.
- 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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