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Articoli e altre risorse sugli Analytics

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.
How health care leaders deployed analytics when crisis hitDuring the COVID-19 pandemic, some health care providers were well-positioned to respond to rapid changes in demand. The factor that most distinguished them was that they already had a strong capacity in place for using data to inform decisions. Read about three key takeaways from their experiences.
Situational awareness guides our responses – routine to crisisMany circumstances call for situational awareness – that is, being mindful of what’s present and happening around you. The COVID-19 pandemic heightened this need, as leaders across industries used analytics and visualization to gain real-time situational awareness and respond with fast, critical decisions.
A data scientist’s views on data literacyGet a data scientist and teacher's perspective on the value of having foundational knowledge so you can more easily tell data fact from data fiction.
Respond, recover and reimagineDisruptions to our lives happen regularly, though most are not as far-reaching as the COVID-19 pandemic. Whatever their nature, it’s helpful to have a plan for how to exit disruption still on your feet and in the game. Learn about the three-phase approach SAS recommends for mitigating widespread disturbances.
Contact tracing investigations for public health: Technology enhances epidemic investigationWhat was once a cumbersome process that relied on an individual’s often incomplete or inaccurate memory, contact tracing investigations for public health has entered the digital era thanks to advanced analytics and data visualization.
From living on the streets to owning a profitable businessZoe Empowers, a ministry for vulnerable children living in life-threatening poverty in Africa and India, finally found a way to measure and reveal its incredible impact. Using SAS, they developed an "empowerment index" that measures improvements in housing, health, education and more for program participants.
Saving lives during a global pandemic through medical resource optimizationCleveland Clinic is operationalizing analytics to combat COVID-19, creating innovative models that help forecast patient volume, bed capacity, medical equipment availability and more.
Will health care be fundamentally changed post-COVID-19?Many market forces are supporting the transformation to virtual digital health programs -- the COVID-19 pandemic is just the latest compelling event.
Jump-start COVID-19 research with text analytics Applying text analytics and AI to discover trends and commonalities among COVID-19 research documents can lead to new insights about the disease and help answer many unanswered questions.
Optimizing well placement to eliminate water poverty How data visualization is helping Water for Good bring fresh water to the Central African Republic.
5 ways to measure beehive health with analytics and hive-streaming dataThis analytical approach to understanding bee hive health can automatically alert beekeepers to changes in hive weights, temperatures, flight activity and more.
Fighting coronavirus: 4 ways analytics is making a differenceCoronavirus has separated us from family, friends, cultural and religious communities. Unfortunately, isolation is essential to slowing the spread of the virus. What else can be done? Learn how analytics is being used to improve responses to the coronavirus outbreak.
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.
How to work like a disrupterFind out what companies like Netflix, Airbnb, Spotify and Lyft know about analytics that you don't know. Learn how to become technologically and analytically mature just like them.
Three steps for conquering the last mile of analyticsPutting your analytical models into production can be the most difficult part of the analytics journey. It’s no surprise that this last mile of analytics – bringing models into deployment – is the hardest part of digital transformation initiatives for organizations to master, yet it’s the most crucial.
Discover a secret resource for working with cloud providersAre you overwhelmed by the hundreds of options and offers in the cloud? Are you finding it hard to select the best cloud services from the different cloud providers? Why not ask a neutral and informed third party for help?
The transformational power of evidence-based decision making in health policyState health agencies are under pressure to deliver better health outcomes while minimizing costs. Read how data and analytics are being used to confront our biggest health care challenges head on.
Operationalizing analytics: 4 ways banks are conquering the infamous ‘last mile’Here are four examples across the banking industry that show how these leading organizations followed a clearly defined path to conquer the infamous 'last mile' of analytics.
ModelOps: How to operationalize the model life cycleModelOps is where analytical models are cycled from the data science team to the IT production team in a regular cadence of deployment and updates. In the race to realizing value from AI models, it’s a winning ingredient that only a few companies are using.
Machine learning: una nuova normalitàPer abbracciare il cambiamento è necessario innovare la tecnologia e cambiare mindset. La cultura della digital transformation deve essere compresa e condivisa.
AI, Machine Learning and Cloud: universities enter the future of Analytics with SAS Viya for LearnersA collaboration between an academic institution and a multinational is already standing out as a success story that connects education and business. The aim is to support students in their data science training, put them to work on real-world projects and give them high in demand, future proof, skills.
AI, Machine Learning e Cloud: con SAS Viya for Learners l’università entra nel futuro degli AnalyticsUn esempio virtuoso di collaborazione tra mondo accademico e impresa per sostenere gli studenti nel processo di trasformazione: studio, formazione e progetti concreti sui dati per creare i professionisti di domani.
From Apollo to AI: A new era of American explorationAs we celebrate the 50th anniversary of the Apollo 11 mission, what’s the next frontier for American Innovation? It’s available now, from our desks and waits for us to unlock its potential.
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.
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.
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.
Le cinque tecnologie di IA che devi assolutamente conoscereConosci la differenza tra intelligenza artificiale (IA) e machine learning? E sapresti spiegare perché la computer vision è una tecnologia IA? Scoprilo in questa breve panoramica.
Bringing data to the streamHow much do we know about fresh water systems and the dynamic nature of streams and rivers? Find out how one data scientist turned his fascination with streams and rivers into a career.
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.
Ci vuole cuore e cervello per portare a terra progetti di machine learning70 studenti di 3 dipartimenti diversi dell’Università Bicocca di Milano si sono sfidati sviluppando un progetto completo di machine learning su dati AC Milan. Due giorni per preparare i dati, sviluppare il modello analitico, e raccontare l’esperienza in modalità data storytelling.
Machine Learning: il cuore matematico dell’intelligenza artificiale tra fiducia e responsabilitàSpesso associamo il machine learning al deep learning come se fossero sinonimi. In realtà Il deep learning è l’insieme di tecniche appartenenti alla famiglia delle reti neurali che sta aiutando a proiettare il machine learning verso il futuro.
Benvenuti nelle assicurazioni 4.0: tutto a portata di clickSecondo i dati di una ricerca condotta da CeTif-Excellence Consulting, nei prossimi mesi/anni l’80% delle compagnie assicurative punterà a investire su customer experience, canali digitali, prodotti e servizi abbinati per rispondere in modo più puntuale alle nuove esigenze del consumatore/assicurato.
Il Machine Learning spiegato a mia nonnaIntelligenza Artificiale come “l’uso di macchine che portano a termine compiti in un modo che consideriamo intelligente” mentre ci si riferisce al Machine Learning come “l’applicazione dell’Intelligenza Artificiale per rendere le macchine libere di accedere a set strutturati di dati ed apprendere da sole”.

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