SAS IS A LEADER
IDC MarketScape: Worldwide Machine Learning Operations Platforms 2022
SAS Model Manager offers support for a wide variety of languages and platforms. It integrates with Git (including GitLab and GitHub), Python, R, MLflow, and Azure Machine Learning, as well as with container registries on Azure, AWS, GCP, and private Docker registries. Customers appreciated this flexibility and capability.
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电子书
How to govern your AI strategy in a highly regulated worldIt’s no longer a case of “if” an organization adopts AI but “when.”
The technology is rapidly advancing and transforming the workplace and society at large, but it comes with risks. That’s where governance comes in. Governance is essential to the reliable, transparent and ethical performance of AI. But the clear lack of oversight of the technology is putting many organizations at risk of noncompliance with incoming regulations around AI, such as the EU AI Act.
This e-book will reveal:
· Why AI governance is so important and what successful governance looks like.
· The five key drivers for implementing AI governance today.
· The risks of poor governance and growing regulatory pressure.
· A practical approach to implementing AI governance.
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白皮书
Boosting Tax Agency Productivity and Protection with AI and Generative AIGenerative AI (GenAI) technology is gaining momentum rapidly, not just in businesses and government agencies, but also among those trying to defraud them. Tax agencies have potentially valuable uses of GenAI in process productivity, taxpayer service, and staying ahead of fraudsters by augmenting fraud detection and threat simulation. Given the new and sometimes uneven capabilities of GenAI, agencies should be approaching it with both purpose and caution. To explore these opportunities and threats, IIA spoke with SAS global tax and revenue compliance experts Teya Dyan, Principal Industry Consultant, based in North America, Ensley Tan, Principal Industry Consultant, based in Asia Pacific, and Alexandre Negadi, Senior Industry Consultant, based in Europe.
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电子书
Your journey to a GenAI future: A strategic path to success in health careGenAI is at the forefront of global health care innovation and is here to stay. Health care organizations at large are leaning into the promise of advanced technologies with the intent to streamline operations and deliver stronger health outcomes for patients all over the world. But in a highly regulated, protected and data-sensitive sector, how is this technology being used? And how will health care organizations keep patient data safe while implementing cutting-edge technologies like GenAI?
In this report, you’ll discover:
• How health care organizations are approaching GenAI adoption compared with other sectors.
• The specific areas where health care already sees GenAI drive results – and where they’re still navigating uncertainty.
• How GenAI investments in health care stack up against other sectors and where these industries are placing their bets.
• Practical strategies to overcome the challenges of GenAI implementation, ensuring you maximize your return on investment (ROI) and stay ahead of the curve.
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网络研讨会
医疗 AI：改善临床治疗和运营决策AI 为医疗保健业带来颠覆性变革。与 SAS 和 Microsoft 一起探索创新的 AI 解决方案，改善患者治疗，提高护理服务效率。
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分析报告
SAS 在 2024 年第三季度《Forrester Wave™：AI/机器学习平台》报告中被评为领导者。 -
分析报告
2024 年《IDC MarketScape：全球决策智能平台》报告 -
分析报告
ARC View：工业级 AI：洞察数据，丰硕成果该 ARC View 报告解释了工业 AI 投资不仅可以使组织马上获得回报，而且可以满足组织的未来需求。
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电子书
Your journey to a GenAI future: A strategic path to success in life sciences and pharmaAs generative AI continues to make waves across both headlines and boardrooms, the life sciences industry is unlocking new possibilities that could reshape the future. This sector, known for managing vast, intricate data sets and safeguarding sensitive patient information, is poised to harness GenAI for groundbreaking advancements. In life sciences, GenAI isn’t just a buzzword – it’s a game changer with the potential to revolutionize innovation, productivity and patient care.
Our latest insights on GenAI come from a comprehensive survey of 1,600 organizations across the globe, offering a deep dive into how different industries are approaching GenAI. Specifically, we focused on the responses of 237 senior life sciences leaders who are at the forefront of shaping GenAI, data and analytics strategy.
In this report, you’ll discover:
• How the life sciences industry is leading or lagging in GenAI adoption compared with other sectors.
• The specific areas where the industry is already seeing GenAI drive results – and where it is still navigating uncertainty.
• How GenAI investments in life sciences stack up against other sectors and where the industry is placing its bets.
• Practical strategies to overcome the challenges of GenAI implementation, ensuring you maximize your return on investment (ROI) and stay ahead of the curve.
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分析报告
IDC MarketScape: Worldwide Machine Learning Operations Platforms 2024 -
白皮书
Revealing the paths to 2040: four possible scenarios for insuranceFrom extreme weather events and natural disasters to geopolitical volatility and shifting demographics, insurers face increasing numbers and varieties of disruptions and uncertainties. At the same time, longstanding risk models are upended by rapid technological advances and evolving market needs. Opportunities abound – but the future is unclear.
This Economist Impact report, informed by expert interviews and an analysis of megatrends, presents insurers with four possible scenarios for the world in 2040. Each path forward describes a potential future, reflecting two main drivers of change:
– Pace of technological evolution.
– Level of global cooperation.
How will insurance evolve? Challenge your assumptions as you delve into these scenarios, considering along the way how you should prepare.
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电子书
A Comprehensive Approach to Trustworthy Data and AI GovernanceAI is revolutionizing human life and unlocking a whole new world of innovation. As AI becomes more prevalent, it will affect nearly every aspect of society from our professional to personal lives. Organizations that can demonstrate responsible and ethical use of AI are more likely to be commercially successful. This is where Trustworthy AI – a system designed to ensure safety, reliability and ethical practices – can help.
Trustworthy AI is an AI system designed, developed and deployed with human-centricity in mind. These systems incorporate appropriate levels of accountability, inclusivity, transparency, completeness and robustness to promote human agency and prevent human harm.
In this eBook you will discover:
The business need for ethics in AI
Why you should embrace Trustworthy AI
How to establish Trustworthy AI governance
The 6 SAS principles to guide your Trustworthy AI strategy
How the SAS Data Ethics Practice supports Trustworthy AI
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电子书
Five reasons developers hit a productivity wall – and what to do about itDevelopers, when you hit a wall, you hit it hard. And it’s often the same five obstacles getting in the way of productivity over and over again. Do these issues sound familiar?
“I don’t have my own space to experiment with models before sharing them.”
“It takes too long to develop a model.”
“The infrastructure we need costs too much.”
“It’s too hard to keep track of version updates.”
“Everybody’s getting different results from the same data sets.”
This e-book from SAS and AWS takes a closer look at each of these obstacles and how you can overcome them with the help of SAS® Viya® Workbench. Make productivity blockers a thing of the past.
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白皮书
Solving the public services productivity puzzleIn Global Government Forum’s survey, 91% of public service respondents said they face a productivity challenge, with 56% characterizing it as significant or very significant.
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电子书
Data-driven health careThe use of technology and data in the health care ecosystem continues to evolve. An extreme emphasis has been placed on digital health, AI, and the need for interoperability across various stakeholders in the healthcare ecosystem. Interoperability of different health care systems and devices to seamlessly exchange information is crucial to provide stronger health outcomes and patient engagement opportunities, enhance patient safety and operational efficiency, and reduce duplicated effort and potential for error.
Discover how health care powered by data and technology will be the springboard to the future.
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电子书
Marketers and GenAI: Diving Into the Shallow EndMarketers are leading in GenAI use, but it’s only surface level. What’s needed to take the next step?
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分析报告
2024 Gartner® 数据科学与机器学习魔力象限™ -
电子书
Your journey to a GenAI future: An insurer’s strategic path to successThe insurance industry is rapidly embracing generative AI technology, recognizing its extraordinary capabilities through high rates of personal and organizational usage. Overwhelmingly, insurance companies around the globe plan to invest in GenAI over the next year, and most have a dedicated budget in place. Yet many lack sufficient budgeting for GenAI governance, and most governance frameworks are still in development.
Recent research compiled survey results from 1,600 global organizations across a wide range of sectors. In this report, we drilled down to the 236 respondents who are senior decision makers in GenAI strategy or data analytics in the insurance sector.
Read the results to understand insurance firms’ unique perspectives on GenAI – including how the industry compares to other sectors, how you can proactively prepare for implementation challenges, what the most promising business opportunities are, and which issues are the top concerns.
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电子书
Your journey to a GenAI future: A strategic path to success for governmentAs generative AI (GenAI) accelerates into the mainstream, organizations of every kind are seeing the transformative potential of the technology. Many government organizations handle huge data sets, hold sensitive personal information and synthesize details about entire populations. For government, GenAI could create a paradigm shift in productivity and capability.
Our research findings are based on a new survey of 1,600 organizations from a wide range of sectors worldwide. To better understand the unique perspectives that government organizations have about GenAI, we examined the responses from the 237 senior leaders who are responsible for making decisions on GenAI strategy or data analytics.
This report uncovers:
• How governments are implementing GenAI compared to other sectors.
• Which areas governments are already seeing the benefits of GenAI and where they feel less confident.
• How government investment stacks up against other sectors and where it’s being spent.
• How you can proactively prepare for the challenges of implementing GenAI to ensure a strong ROI
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客户案例
Conservation efforts take flight with analyticsThe Royal Society for the Protection of Birds uses SAS to help safeguard wildlife.
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电子书
Public service of the futureNever before have governments been asked to do so much, so fast, while facing considerable pressures – rising customer service expectations, fiscal constraints, overstretched organizations and workforce fatigue.
Technologies like AI and generative AI are shifting the limits of what is possible – enabling fresh ideas about how public sector organizations can deliver services and helping to rethink what services are offered. From national to local government, law enforcement to health and defense to education, great strides are being made to deliver better outcomes and experiences.
In this e-book, you will discover six considerations for improving productivity and ensuring public servants have the time to focus on what matters. Here's a sneak peek:
· How do different demographics engage with public services and how do you serve everyone?
· Are traditional processes meeting your organization’s needs? Would updating and modernizing help you achieve increased operational efficiency?
· How AI is a catalyst for organizational transformation.
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白皮书
Pioneering Ethical AI: The Crucial Role of Property and Casualty InsurersInsurers have long been global leaders in addressing risks and protecting people and businesses. As artificial intelligence continues to revolutionize how business gets done, it is redefining how insurers can deliver on their promises. Read this paper to learn from industry veterans and AI experts alike about:
• The state of AI regulations globally.
• The multifaceted role insurers can play in developing AI ethics.
• Why insurers are uniquely qualified to use AI (and GenAI) – and how they’re using these technologies today.
• An approach to an ethical AI framework that any insurer can follow to establish their own AI narrative.
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客户案例
Advanced analytics empowers businesses with data-driven decisionsThe Hang Seng University of Hong Kong uses SAS Viya to nurture next-generation analytical talent and aid small to mid-size businesses.
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电子书
On the Road to Accelerating Claims AutomationMore than ever, insurance companies need to provide customers with seamless interactions that save them time, minimize hassle, and make them feel seen, understood, and cared for. Many are also exploring the use of AI for claims prevention – for example, by creating new risk mitigation services. All of this requires investment in digital technologies that work together to enable intuitive, Amazon-like customer experiences. This ebook explores how insurers can make the leap to digitally transformed, intelligent claims processes that customers love and increase operational efficiency and reduce costs.
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分析报告
SAS is a Leader in The Forrester Wave™: AI Decisioning Platforms, Q2 2023.The Forrester Wave™: AI Decisioning Platforms, Q2 2023 recognizes SAS for seamlessly integrating world-class analytics for decisioning.
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白皮书
How to realize value from cloud analytics faster — and with less cost and riskIn just a few years’ time, analytic and AI models have gone from being on-premises “pet projects” and proofs of concept to high-volume mission-critical technologies developed and deployed in the cloud to support business decisions at scale. But as Foundry’s survey reveals, most IT departments haven’t evolved how they will support and enable the new world of cloud analytics at scale.
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白皮书
Top 5 insurance problems – and AI isn’t one of themAs all players in the insurance ecosystem know – insurers to reinsurers, GSIs and regulators – the industry faces a multitude of daunting business problems today. In this paper, we discuss five of the most pressing insurance problems, how they affect communities around the world, and obstacles that can get in the way of solving those challenges. Read the paper to learn how insurers can use AI to identify and solve far-reaching issues. And learn why it will take the entire insurance ecosystem to course correct on business results, climate risk, AI safety and governance, and more.
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客户案例
Transformation of the National Bank of Greece with SAS Viya on Microsoft AzureLeading Greek financial institution pursues digital transformation backed by advanced analytics to become the bank of choice for businesses and private individuals.
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客户案例
Finland’s top retail bank applies AI to improve customer service and credit scoringS-Bank provides better customer service and faster, more accurate loan processing time using SAS Viya on Azure.
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客户案例
Complex telco product portfolio, maximum agility thanks to intelligent decisioningGerman telco provider 1&1 works with SAS and partners to improve offer management, accelerate time to market and enhance the customer experience.
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客户案例
Predictive analytics and AI deliver a winning fan experience The Orlando Magic uses mobile app data and machine learning to personalize marketing campaigns and analyze game data.
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客户案例
Managing Dutch roads and waterways with intelligenceA modern AI, IoT and analytics platform powered by SAS Viya helps Rijkswaterstaat move from reactive to predictive infrastructure maintenance.
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客户案例
Transforming the consumer banking experience through advanced analyticsCIMB Singapore uses SAS Viya to enhance business operations and keep pace with changing customer needs.
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客户案例
Building reliability in riskBanca Mediolanum uses SAS Viya to develop high-performing, reliable credit scoring models.
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客户案例
It’s all in the research: Using AI to solve issues in health careWith the University of Alberta's new health data management and analysis platform, DARC, it can now increase research capacity and provide high-performance computing and data storage in a secure environment. SAS provided the university software to help make its platform thrive amidst a global pandemic.
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客户案例
Jakarta Smart City uses IoT analytics to better serve residentsJakarta and SAS team up to create an award-winning approach to public services and disaster management.
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客户案例
Improving data collection and modeling to accelerate predictive medicine effortsDompé farmaceutici uses SAS for predictive analytics and quantitative disease modeling.
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客户案例
Revolutionizing marketing campaigns with AIAlliant relies on machine learning to create qualified marketing audiences for its clients.
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电子书
Intelligent decisioning in governmentGovernments can incorporate AI-driven decisioning into existing business processes to take advantage of digital transformation benefits. Through automated processes, deeper insights and the ability to act quickly, governments can innovate service delivery, drive efficiency and help build a better future.
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电子书
Government navigating an uncertain worldHow governments can harness data,
advanced analytics, and trustworthy AI to
prepare for the unexpected—and respond
faster to protect and improve citizens’ lives.
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白皮书
Generative AI in Health Care: Opportunities and CautionsLearn how GenAI will affect all aspects of health care, from cost containment to patient care., and the importance for organizations to recognize both the potential and the limits of this new technology and be alert to how it’s being used to perpetrate fraud.
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客户案例
AI helps students graduate from collegeHillsborough (FL) Community College uses SAS® Visual Analytics to determine what students need to complete their degrees
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电子书
Detect and halt risky payments across the life sciences supply chainCut fraud, waste, error and abuse with a data-driven approach to payment integrity
It’s estimated that 4.57% of the total annual procurement spending in the private sector is lost to fraud and error. What would be the impact to life sciences organizations if you could stop that flow of cash out of the business? Even for smaller organizations, improving payment integrity could free up significant capital for strategic investments. In R&D, for example, it could free up funds for strategic acquisitions or returning cash to shareholders.
In this e-book, we’ll look at how a smarter, more data-driven approach to payment integrity helps life sciences companies gain faster and deeper visibility into their spending across R&D, manufacturing and distribution. A data-driven approach also helps highlight potential anomalies in real time for investigation by human experts.
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客户案例
智慧城市携手分析技术和物联网技术来预测、管理洪水事件北卡罗来纳州凯里镇与 SAS 和 Microsoft 合作，保护市民免遭洪灾、保护水域并促进城市的环保发展。
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文章
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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电子书
The insurance data and AI revolutionInsurers face continual disruptions these days as they respond to price sensitivity, the push for sustainable practices, evolving regulations, climate change issues and all types of heightened risks. How should they respond?
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分析报告
IDC Spotlight: Looking Beyond the AI Model to Improve the Value of Computer Vision in Manufacturing OperationsThis IDC Spotlight explores the increasing adoption of computer vision (CV) by manufacturers, and how in order to succeed, they must focus on more than just model development, validation and deployment. SAS delivers a comprehensive portfolio of tools, software and resources – integrated into SAS Viya – to develop and deploy CV solutions.
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文章
5 machine learning mistakes and how to avoid themMachine learning is not magic. It presents many of the same challenges as other analytics methods. Learn how to overcome those challenges and incorporate new techniques into your analytics strategy.
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电子书
5 Steps to Accelerate Value From Your Industrial IoT Data This e-book features five steps industrial leaders can follow to get more value from IIoT data. It describes how to craft a comprehensive IIoT strategy, what to look for in an edge-to-enterprise analytics solution, and how to evaluate IIoT solutions.
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客户案例
French national rugby team boosts performance with AI and analyticsThe French Rugby Federation counts on intelligence gleaned from SAS Viya on Microsoft Azure to guide coaching decisions and enhance player performance.
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客户案例
客户案例
Advanced analytics helps policymakers determine how new tax measures would affect citizensAscertaining the ‘winners’ and ‘losers’ of potential tax changes before regulations are implemented.
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客户案例
Taking the guesswork out of production planningEuramax uses SAS to prevent production delays
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文章
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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客户案例
Transforming steelmaking through IoT analyticsSSAB improves production efficiency, product quality and maintenance strategies using sensor data, artificial intelligence and advanced analytics.
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分析报告
SAS is a Leader in The Forrester Wave™: Digital Intelligence Platforms, Q4 2022SAS is a Leader in The Forrester Wave™: Digital Intelligence Platforms, Q4 2022.
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客户案例
Analytics helps major public health system run efficient programs and improve patient careThe Los Angeles County Department of Health Services relies on advanced analytics from SAS to meet federal regulations, ensure financial viability and better serve a diverse population of more than 10 million people.
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客户案例
Predictive analytics helps save lives during COVID-19 pandemicFPS Public Health uses SAS to forecast hospital bed occupancy, predict infection rates and ensure sufficient medical staffing during global health crisis.
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客户案例
World’s largest sports and humanitarian event builds legacy of inclusion with data-driven technologySpecial Olympics World Games Abu Dhabi uses SAS® Analytics and AI solutions to keep athletes safe and fans engaged.
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文章
Data lineage: Making artificial intelligence smarterLear how data lineage plays a vital role in understanding data, making it a foundational principle of AI.
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文章
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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分析报告
Gartner® Top Strategic Technology Trends for 2024: AI Trust, Risk and Security ManagementLearn why IT leaders must adopt an AI TRiSM to protect their organizations and improve their business outcomes from AI models.
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文章
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.
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白皮书
Artificial Intelligence for ExecutivesThis paper outlines the SAS approach to AI and explains key concepts. It also provides process and implementation tips if you are considering adding AI technologies to your business and analytical strategies.
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文章
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.
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文章
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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文章
Wanted: AI leadersDo you have what it takes to be an AI leader? In this growing field, people skills, innovation and ethics are more important than expertise in artificial intelligence technologies.
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文章
Exploring the sun with big dataResearchers working for NASA are using automatic, exploratory and visual analysis of big data to help understand the mysteries of our universe.
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文章
When it matters: Safeguarding your organization from the insideWith evolving threats, fraud detection technologies have to be flexible and nimble, and automated risk detection is a crucial component of decision advantage.
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分析报告
IDC MarketScape: Worldwide Responsible Artificial Intelligence for Integrated Financial Crime Management Platforms 2022 Vendor AssessmentLearn why SAS is positioned in the Leaders category in the 2022 IDC MarketScape for worldwide responsible artificial intelligence for integrated financial crime management platforms.
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文章
5 steps to sustainable GDPR complianceFollow these steps to achieve GDPR compliance by the May 2018 deadline – and get added benefits along the way.
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分析报告
Matrix: Leading Fraud & AML Machine Learning PlatformsSAS is a best-in-class vendor in the most recent Datos Insights report, Matrix: Leading Fraud & AML Machine Learning Platforms.
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白皮书
Machine Learning With SAS® Enterprise Miner™Learn how SAS modelers prepared data and applied different machine learning techniques to create and identify the most accurate model for predicting churn using KDD Cup data.
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文章
Machine learning for beginners and beyondWhether you’re an experienced data scientist or a machine learning beginner, you’ll appreciate these 10 tips for getting started with machine learning.
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文章
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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白皮书
The Machine Learning LandscapeThis paper, for novice and intermediate data scientists, talks about the four widely recognized machine learning styles and their common uses, data and modeling methodologies, and popular algorithms for solving machine learning problems.
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白皮书
Machine Learning Use Cases in Financial CrimesLearn 10 proven ways machine learning can boost the efficiency and effectiveness of fraud and financial crimes teams – from data collection to detection to investigation and reporting.
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白皮书
Machine learning and artificial intelligence in a brave new worldMachine learning in the last few decades has given way to an AI revolution. From self-driving cars to virtual assistants, learn more about the endless possibilities for these developing technologies.
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客户案例
Making buildings – and business – more secure with analytics and AIIndustrial company Comelit Group harnesses the power of SAS Viya 4 to modernize how decisions are made, combining the most successful analytics and AI platform with the flexibility and scalability of the cloud.
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分析报告
SAS Inside Intelligence 2023 ConferenceThis IDC Link focuses on SAS' responsible innovation initiative and the importance of building trust, transparency and information privacy in machine learning and AI life cycle technologies and applications.
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文章
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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文章
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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文章
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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文章
大数据分析在医疗领域发力：阻击寨卡病毒 对抗癌症如何阻止全球疾病的爆发，答案也许就在与疾病有关的数据中以及它是如何传播的。
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客户案例
Just add data: How data and technology — paired with a human touch — create a sustainable and quality culinary experienceBarilla, the world’s largest pasta manufacturer, uses advanced analytics and AI to track global inventory and optimize orders and deliveries to meet surging demand.
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文章
Applying machine learning to IoT dataLet’s move beyond theoretical discussions about machine learning and the Internet of Things – and talk about practical business applications instead.
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客户案例
Manufacturing smarter, safer vehicles with analyticsKia Motors America relies on advanced analytics and artificial intelligence solutions from SAS to improve its products, services and customer satisfaction.
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白皮书
Improve Customer Experience with Actionable Artificial Intelligence While more marketers turn to artificial intelligence technologies, this new territory also raises more questions. This paper offers a detailed look into how AI works, and explores the opportunities and challenges it presents.
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客户案例
Advanced analytics in the cloud helps international biopharmaceutical group enhance operations and efficiencyChiesi Group uses SAS Viya on SAS Cloud hosted on Microsoft Azure to analyze information in a collaborative platform, streamline processes and efficiently deliver trial results to regulatory authorities.
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白皮书
The Next Analytics Age: Machine LearningWhat management and leadership challenges will the next wave of analytic technology bring? This SAS-sponsored Harvard Business Review Insight Center on HBR.org went beyond the buzz to talk about how machine learning will change companies and the way we manage them.
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白皮书
How to Do Deep Learning With SAS® Get an introduction to deep learning techniques and applications, and learn how SAS supports the creation of deep neural network models.
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白皮书
Data Management for Artificial IntelligenceWhen machines learn from exposure to data, the truism of “garbage in, garbage out” for data is truer than ever. Now is the time for executives, particularly the chief data officer, to establish the data management strategy, technology and best practices to ensure success with machine learning.
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研究
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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白皮书
The 3 R’s of AI Adoption: Refactor, Reinvent, ReimagineLearn how organizations are using AI to refactor, reimage and reinvent business as usual. Understand the relative impacts on business process, analytics and data practices, and DevOps at each level of adoption.
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文章
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.
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文章
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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客户案例
University uses analytics to ensure student successWestern Kentucky University uses data visualization and advanced analytics to make informed decisions.
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分析报告
Artificial Intelligence In Retail: What Now?This RSR Benchmark Report examines retailers’ attitudes about AI/ML technology and whether it can be used to turn data into insights and help retailers better understand the environments they operate in.
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分析报告
IDC MarketScape: Worldwide MLOPs Platforms 2022 Vendor AssessmentSAS is positioned in the Leader's category in the 2022 IDC MarketScape for worldwide machine learning operations platforms.
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分析报告
Advanced Analytics Excellence In Discrete ManufacturingThis paper explains how advanced analytics helps discrete manufacturing achieve operational excellence, including potential benefits, the capabilities an organization needs, and how the organization can align with this approach.
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分析报告
Maximizing Innovation in Digitally Maturing Process ManufacturingThis report outlines the roadmap that digitally maturing process manufacturers must follow to identify and build the core competencies needed to use transformation as a competitive advantage.
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分析报告
SAS Explore 2022 Review and AnalysisThis IDC Link focuses on several SAS announcements supporting faster time-to-value for AI/ML model-driven businesses.
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白皮书
What You Need to Know About Data & Digital TransformationCompanies need to know how to use data to meet client needs, hire the right talent, measure performance and communicate their brand’s promise. This collection will cover how to adopt and analyze data and use it as part of your digital transformation.
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白皮书
The Artificial Intelligence of Things We’re living in a world that has more connected devices than humans. See how AI amplifies the value and potential of this fast-growing Internet of Things.
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白皮书
AIOT: How IoT Leaders Are Breaking Away (IDC Market Report / AIoT Survey 2019)Read the results of a global study conducted by IDC, which revealed that AI and the IoT are having a bigger-than-expected impact – and leaders report that the AIoT is becoming the key to competing effectively.
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白皮书
Statistics and Machine Learning at ScaleDiscover how machine learning can be applied to a variety of applications, and learn about the techniques required to help computers learn from massive amounts of data.
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白皮书
Redefine Your Analytics Journey With Interactive Data Exploration and Predictive AnalyticsWhat if your analytics journey were easier? It can be, in five easy steps. Learn how SAS Visual Analytics and SAS Visual Statistics together can provide a fast, fun way to explore data, build models and find the best performer.
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白皮书
Get the most from your AI investment by operationalizing analyticsAnalytics needs to take a page from application development (DevOps) and embrace ModelOps – a practice that puts in place the culture, process and technology to operationalize analytics faster and more efficiently. ModelOps ensures maximum business impact from analytics, automates repeatable tasks, builds collaboration between stakeholders and streamlines the flow of analytics into decision making processes.
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白皮书
AI for the CIO: 10 Tips for SuccessThis paper offers 10 tips for the CIO who is knee-deep in digital transformation projects that require deploying AI models at an enterprise scale.
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白皮书
Building the Data-Intelligent Enterprise: Tap the Power of Technology and PartnersThe value of an intelligent enterprise is clear, but operationalizing analytics can be a long and complex journey. There is no magic bullet or singular solution. Rather, it takes the support of strategic partnerships to create a cohesive strategy and deployment road map that will accelerate deployment and maximize value from analytics investments.
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电子书
How to Take AI Projects From Start to WinThe four pillars of starting a successful AI program and examples of how other organizations have taken their AI projects from start to finish.
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白皮书
How AI Changes the RulesReaping the benefits of AI will require changes in workplace structures, technology strategies and technology governance. Read on to learn more about the changes that leaders must prepare for to successfully implement trusted AI.
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白皮书
AI Momentum, Maturity & Models for Success: Focus on SingaporeAdvances in data and analytics have enabled early adopters of AI to grow beyond experiments and quick hits and provide examples for paths to success with AI.
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电子书
Operationalizing AnalyticsExplore how to overcome difficulties related to data and operationalizing analytics. We’ll also look at how one industry – banking – has been able to realize the full benefit of its analytics investment.
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电子书
Mastering Model Lifecycle OrchestrationThis interactive guide describes the stages of the model life cycle and explains why organizations should embrace different programming languages, tools, techniques and runtime environments when developing and deploying models.
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电子书
Accelerate and improve business outcomes with AIoTOrganizations across multiple industries are using AIoT to improve quality, maximize equipment performance, improve efficiencies and more. Download this e-book to find out how you can reap the same benefits.
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电子书
Formidable ForecastsWith artificial intelligence capabilities and traditional forecasting processes, it’s possible to create efficiencies by automating the production of large-scale time-series analyses and hierarchical forecasts.
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电子书
Fearless Decision? The most successful banks of the future will be those who can see their customers as individuals, appreciate their unique journeys and make decisions accordingly — across all associated business functions.
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白皮书
Adopting AI: The Impacts of AI on ManagementThe AI revolution is no longer the stuff of science fiction – it’s corporate reality. Harvard Business Review’s AI Adoption Insight Center articles on management discuss the reality of AI execution in businesses today and what we’re learning as AI advances.
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白皮书
Adopting AI: Strategic Takes on AI AdoptionA successful AI implementation requires a strong strategy from the beginning. Knowing how and where to fit AI into your business to gain the most benefits is crucial to drive growth.
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白皮书
Adopting AI: Industry PerspectivesFrom self-driving cars to supply chain jobs, detecting crime and changing healthcare, AI promises to transform our business world. The promise of AI is no longer speculative—it’s today’s reality.
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白皮书
Adopting AI: Linchpins of AI Success - Data Scientists and Their Algorithms The Harvard Business Review’s AI Adoption Insight Center focuses on the the human faces behind the computational and automation advancements that are carrying our world into exciting, uncharted territory.
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白皮书
AI Momentum, Maturity and Models for SuccessSAS, Intel and Accenture, working with Forbes Insights, surveyed business leaders and interviewed thought leaders around the world to identify early adopters and uncover emerging best practices for AI. Find out what they had to say.
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白皮书
TDWI Checklist Report Six Best Practices to Ignite the Customer Experience with IoTcustomer data, IoT
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白皮书
The Autonomous Grid in the Age of the Artificial Intelligence of ThingsExplore how AI and IoT work together to deliver everything from improved threat detection to better customer engagement for utilities.
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白皮书
Artificial Intelligence in Banking and Risk ManagementGlobal Association of Risk Professionals (GARP) and SAS survey drew more than 2,000 responses from across the financial services industry to answer questions about the current and future state of AI in risk.
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白皮书
Data, Analytics & AI: How Trust Delivers ValueThe annual Data and Analytics Global Executive Study with MIT Sloan Management Review looks at how 2,400 global business leaders make decisions based on analytics insights.
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白皮书
Combining Robotic Process Automation and Machine LearningLearn how you can make robotic process automation smart by adding machine learning to it.
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白皮书
The Risks and Rewards of AIExploring the rise of AI, Harvard Business Review has published a collection of articles assessing the opportunities and pitfalls that could evolve, with discussions on the innovative uses of data and analytics, industry adoption, impacts to human work, and the factors of business change.
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白皮书
Advanced Analytics: Moving Toward AI, Machine Learning, and Natural Language Processingadvanced analytics, artificial intelligence, machine learning, natural language processing
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白皮书
TDWI Navigator Report: Predictive AnalyticsPredictive Analytics
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电子书
Powering Health Innovation with AIThere is no doubt: AI has the potential to transform health care. The most recent SAS Hackathon showcased how the transformative power of analytics can spark health care innovation. The Hackathon was entirely conducted on a Microsoft Azure cloud infrastructure to facilitate the agile analysis and visualization of big data.
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白皮书
ModelOps with SAS and MicrosoftThis paper explores how SAS and Microsoft have built integrations between SAS Model Manager and Microsoft Azure Machine Learning.
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电子书
The Innovator's Flight Plan to AIAs an emerging technology, AI is naturally associated with innovation. Many organizations are using AI to develop new products and business models, and to improve their business processes.
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电子书
Augmented Analytics: The secret ingredient to better business intelligenceAugmented analytics breaks down the limitations of
business intelligence (BI) and brings forward insights
from data using AI and machine learning.
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客户案例
Predictive analytics empowers bank to act quickly with confidenceOTP Bank Romania can better assess risk, meet profitability targets and enhance customer satisfaction through a streamlined data mining process from SAS.
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文章
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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文章
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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分析报告
dbInsight: SAS Viya is living large on AzureLearn how Azure provides the onramp to a new customer base to take advantage of SAS capabilities without having to make big enterprise software commitments.
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文章
Fraud detection and machine learning: What you need to knowMachine learning and fraud analytics are critical components of a fraud detection toolkit. Here’s what you’ll need to get started – from integrating supervised and unsupervised machine learning in operations to maintaining customer service while defending against fraud.
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文章
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.
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文章
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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文章
An executive’s guide to cognitive computingCognitive computing is the latest buzzworthy term that everyone seems to be talking about in the technology industry. But can machines really think?
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客户案例
Real-time analytics helps telecom provider adapt to changing customer needs during global pandemic and beyondTelefónica Ecuador accelerates digital transformation, improves campaigns and achieves growth via intelligent decisioning powered by SAS.
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客户案例
Advanced analytics can detect and prevent insurance fraud before losses occurYdrogios Insurance limits damage, reduces costs and shields its competitive advantage with SAS® Detection and Investigation for Insurance.
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文章
The untapped potential in unstructured textText is the largest human-generated data source. It grows every day as we post on social media, interact with chatbots and digital assistants, send emails, conduct business online, generate reports and essentially document our daily thoughts and activities using computers and mobile devices.
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客户案例
A model of institutional research champions the value of analytics for allOklahoma State University uses SAS to create an analytics culture and increase student success.
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文章
Student lands dream job with help from SASA strong partnership between the University of Alabama and SAS put Cameron Jagoe on a path that led to his dream job with US Bank.
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客户案例
用机器学习寻找你的最佳客户Seacoast Bank 利用 SAS Viya 上的 AI 和 SAS Visual Analytics 增加客户价值。
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客户案例
Building a decision support systemSAS Business Analytics helps DES generate and analyze key statistical reports, saving time and leading to more effective socioeconomic decision making.
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客户案例
Knowing the who, informs the whatThe New Zealand Ministry of Health established the Virtual Data Registry to more accurately identify diabetes sufferers and citizens likely to contract diabetes. They'll use the database to inform policy and spending decisions that will ensure better care for those patients.
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客户案例
Child support agency uses analytics to provide better options for parentsCalifornia’s Orange County Child Support Services uses analytics from SAS to empower caseworkers to help parents make decisions that benefit their children.
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客户案例
Building a culture of analytics empowers university to lead as an educational enterpriseFrom enrollment to graduation, the University of Texas at Arlington uses SAS Analytics for Education on Amazon Web Services to aid in analysis supporting student success and campus strategic decision making.
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客户案例
Using artificial intelligence to better engage with customersDaiwa Securities uses analytics and machine learning from SAS to better meet customer needs.
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文章
Introduction to machine learning: Five things the quants wish we knewMachine learning is gaining momentum thanks to bigger, more complex data sets. How does it work? Kimberly Nevala from SAS Best Practices explains what it is by focusing on what it isn't.
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文章
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.
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网络研讨会
SAS® Viya® and the cloud: How SAS is changing the game it inventedJoin this webinar to learn how to make the most of cloud migration with SAS Viya.
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客户案例
Travel and tourism forecasts become more accurate with analyticsDER Touristik builds web-based planning tool with SAS to better predict future demand and quickly react to changes in the market.
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文章
如何发现共同购买点希望保持领先CPP并控制欺诈成本的银行需要实施高级反欺诈技术
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客户案例
人工智能和 IoT 分析助力飞机顺利执行重要任务Lockheed Martin 借助 SAS 平台彻底改变了飞行器的维护。
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文章
人工智能、机器学习、深度学习及其他人工智能、机器学习、深度学习都在改变我们的生活和工作方式。它们是如何关联，又是如何改变我们这个世界的？
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文章
Machine learning, data science and AI meet IoTIn this video, Kirk Borne and Michele Null discuss the intersection of machine learning, AI and data science with IoT data and analytics.
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客户案例
Forecasting accuracy brings ‘new energy’ to CameroonEnergy supplier Eneo balances supply and demand to boost efficiency, save millions and improve reliability with SAS Energy Forecasting.
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客户案例
IoT 数据和人工智能可减少停机时间，帮助卡车司机持续完成运输工作沃尔沃卡车和马克卡车使用传感器数据和 SAS AI 解决方案，最大程度地减少意外停机时间。
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文章
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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文章
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.
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文章
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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文章
AI in government: The path to adoption and deploymentThe government sector is lagging in AI adoption, but awareness of the importance of AI in the public sector is increasing. Our survey indicates that operational issues are requiring governments to turn their attention to AI projects as a way to address important public issues.
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文章
AI in manufacturing: New opportunities 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.
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文章
What do drones, AI and proactive policing have in common?Law enforcement and public safety agencies must wrangle diverse data sets – such as data from drones – in their proactive policing operations. To be most effective, they need modern tools that support AI techniques like machine learning, computer vision and natural language processing.
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文章
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.
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文章
As AI accelerates, focus on 'road' conditionsAI technology has made huge strides in a short amount of time and is ready for broader adoption. But as organizations accelerate their AI efforts, they need to take extra care, because as any police officer will tell you, even small potholes can cause problems for vehicles traveling at high speeds.
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文章
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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文章
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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文章
Your personal data scientistImagine pushing a button on your desk and asking for the latest sales forecasts the same way you might ask Siri for the weather forecast. Find out what else is possible with a combination of natural language processing and machine learning.
IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of ICT suppliers in a given market. The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each vendor’s position within a given market. The Capabilities score measures vendor product, go-to-market and business execution in the short-term. The Strategy score measures alignment of vendor strategies with customer requirements in a 3-5-year timeframe. Vendor market share is represented by the size of the icons.