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.
Explore More SAS Resources
To browse resources by type, select an option below.
-
- Select resource type
- 분석 보고서
- E-BOOK
- 백서
- 백서
- 기사
- 블로그 게시물
- 책 발췌
- 사례 연구
- 인포그래픽
- 회견
- R E S E A R C H
- 시리즈
- 동영상
- 웨비나
- 고객 사례
-
E-BOOK
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.
-
백서
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.
-
고객 사례
Advanced analytics in the cloud helps international biopharmaceutical group enhance operations and efficiencyChiesi Group uses SAS Viya to analyze information in a collaborative platform, streamline processes and efficiently deliver trial results to regulatory authorities.
-
기타 – 제3자
백서
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.
-
고객 사례
AI helps students graduate from collegeHillsborough (FL) Community College uses SAS® Visual Analytics to determine what students need to complete their degrees
-
백서
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.
-
E-BOOK
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.
-
고객 사례
분석과 IoT로 홍수를 예측 및 관리하는 스마트 도시미국 노스캐롤라이나 주의 소도시 캐리(Cary)는 SAS 및 Microsoft와 협력하여 홍수로부터 시민을 보호하고, 환경친화적인 개발을 이끌고 있습니다.
-
기사
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.
-
E-BOOK
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?
-
고객 사례
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.
-
분석 보고서
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.
-
기사
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.
-
E-BOOK
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.
-
고객 사례
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.
-
고객 사례
Breaking the cycle of poverty through advanced analyticsCompassion International uses advanced analytics to help millions of children from impoverished nations secure food, medical care and educational resources to grow, learn and thrive.
-
고객 사례
고객 사례
Advanced analytics helps policymakers determine how new tax measures would affect citizensAscertaining the ‘winners’ and ‘losers’ of potential tax changes before regulations are implemented.
-
고객 사례
Taking the guesswork out of production planningEuramax uses SAS to prevent production delays
-
기사
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.
-
고객 사례
Transforming steelmaking through IoT analyticsSSAB improves production efficiency, product quality and maintenance strategies using sensor data, artificial intelligence and advanced analytics.
-
분석 보고서
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.
-
분석 보고서
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.
-
고객 사례
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.
-
고객 사례
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.
-
고객 사례
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.
-
고객 사례
SAS를 통해 고객 참여를 활성화하는 호주 최대 이동통신사 TelstraAustralia’s largest telecommunications company relies on SAS Analytics to better understand customers’ needs and develop the products and services they want.
-
기사
Data lineage: Making artificial intelligence smarterLear how data lineage plays a vital role in understanding data, making it a foundational principle of AI.
-
기사
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.
-
분석 보고서
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.
-
고객 사례
Transforming the consumer banking experience through advanced analyticsCIMB Singapore uses SAS Viya to enhance business operations and keep pace with changing customer needs.
-
기사
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.
-
백서
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.
-
기사
인공 지능의 인간미글로벌 문제를 해결하기 위해 인공 지능과 인간이 힘을 모으면 어떻게 될까?
-
기사
Machine learning and artificial intelligence in a brave new worldWhat is the interplay between man and machine in a brave new world with AI?
-
기사
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.
-
기사
Artificial intelligence, machine learning, deep learning and moreArtificial intelligence, machine learning and deep learning are set to change the way we live and work. How do they relate and how are they changing our world?
-
기사
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.
-
기사
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.
-
분석 보고서
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.
-
기사
5 steps to sustainable GDPR complianceFollow these steps to achieve GDPR compliance by the May 2018 deadline – and get added benefits along the way.
-
고객 사례
Conservation efforts take flight with analyticsThe Royal Society for the Protection of Birds uses SAS to help safeguard wildlife.
-
분석 보고서
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.
-
백서
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.
-
기사
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.
-
기사
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
고객 사례
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.
-
분석 보고서
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.
-
기사
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.
-
기사
4 strategies that will change your approach to fraud detection기술의 발전에 힘입어 금융 기관들은 그 어느 때보다 우수한 사기 탐지 기능으로 무장하고 있습니다. 방어망를 대폭 강화할 수 있는 4가지 방법을 소개합니다.
-
기사
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.
-
기사
Stopping the Zika virus: The potential of big data, analyticsHow do you stop global outbreaks? The answer may be in the data about the disease and how it spreads.
-
고객 사례
고객 사례
IoT data with artificial intelligence reduces downtime, helps truckers keep on truckingVolvo Trucks and Mack Trucks use sensor data and SAS AI solutions to minimize unplanned downtime.
-
고객 사례
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.
-
고객 사례
Improving data collection and modeling to accelerate predictive medicine effortsDompé farmaceutici uses SAS for predictive analytics and quantitative disease modeling.
-
기사
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.
-
고객 사례
Azure 환경에서 SAS Viya를 통해 디지털 혁신을 추구하는 그리스의 선도 금융 기업Leading Greek financial institution pursues digital transformation backed by advanced analytics to become the bank of choice for businesses and private individuals.
-
고객 사례
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.
-
고객 사례
고급 분석으로 고객 경험 개선은행들은 고객에게 더 나은 서비스를 제공하고 고객을 유지 및 확보할 수 있는 새로운 방법을 찾기 위해 도전하고 있습니다. Seacoast Bank는 SAS Viya와 SAS Visual Analytics를 활용하여 은행이 보유하고 있는 수많은 고객 데이터로부터 고객의 요구와 요구에 대한 통찰력을 얻을 수 있었습니다.
-
고객 사례
고객 만족을 높이는 새로운 은행 개념스코틀랜드 왕립 은행이 데이터 중심의 의사 결정을 통해 조직 프로세스를 혁신적으로 바꾸고 직원 참여도를 개선하며 훌륭한 고객 서비스를 제공하고 있는 방법에 대해 확인하십시오.
-
고객 사례
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
R E S E A R C H
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.
-
백서
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.
-
기사
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.
-
기사
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.
-
분석 보고서
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.
-
분석 보고서
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.
-
고객 사례
Financial lender cuts third-party fraud by more than 80% with layered detectionAxcess Financial uses SAS Identity 360 to dramatically reduce fraud losses and boost customer satisfaction.
-
분석 보고서
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.
-
분석 보고서
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.
-
분석 보고서
SAS Explore 2022 Review and AnalysisThis IDC Link focuses on several SAS announcements supporting faster time-to-value for AI/ML model-driven businesses.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
E-BOOK
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.
-
백서
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.
-
백서
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.
-
E-BOOK
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.
-
E-BOOK
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.
-
E-BOOK
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.
-
E-BOOK
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.
-
E-BOOK
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.
-
E-BOOK
Transformational decision?Governments 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.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
TDWI Checklist Report Six Best Practices to Ignite the Customer Experience with IoTcustomer data, IoT
-
백서
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.
-
백서
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.
-
백서
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.
-
백서
Combining Robotic Process Automation and Machine LearningLearn how you can make robotic process automation smart by adding machine learning to it.
-
백서
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.
-
백서
Advanced Analytics: Moving Toward AI, Machine Learning, and Natural Language Processingadvanced analytics, artificial intelligence, machine learning, natural language processing
-
백서
TDWI Navigator Report: Predictive AnalyticsPredictive Analytics
-
E-BOOK
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.
-
백서
ModelOps with SAS and MicrosoftThis paper explores how SAS and Microsoft have built integrations between SAS Model Manager and Microsoft Azure Machine Learning.
-
E-BOOK
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.
-
E-BOOK
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.
-
고객 사례
Artificial intelligence yields breakthrough innovation in crop scienceBoragen partners with SAS to fight plant disease, protect crops and boost agricultural production sustainably.
-
분석 보고서
SAS, 가트너 MQ ‘데이터 사이언스·머신러닝 플랫폼’ 부문 7년 연속 리더SAS는 ‘2020년 가트너 매직 쿼드런트: 데이터 사이언스 및 머신러닝 플랫폼 부문’ 보고서에서 비전 완성도 및 실행력을 인정받아 리더로 선정됐습니다. 가트너는 SAS의 강점으로 높은 브랜드 신뢰성, 업계 최고의 모델 운영 및 관리, 자동화된 사용 편의성 및 부가 기능 등을 꼽았습니다.
-
고객 사례
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.
-
기사
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.
-
고객 사례
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.
-
분석 보고서
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.
-
고객 사례
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.
-
기사
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.
-
기사
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.
-
기사
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?
-
기사
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?
-
고객 사례
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.
-
고객 사례
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.
-
기사
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.
-
기사
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.
-
고객 사례
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.
-
기사
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.
-
고객 사례
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.
-
고객 사례
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.
-
고객 사례
Using artificial intelligence to better engage with customersDaiwa Securities uses analytics and machine learning from SAS to better meet customer needs.
-
기사
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.
-
기사
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.
-
웨비나
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.
-
고객 사례
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.
-
고객 사례
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.
-
기사
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.
-
기사
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.
-
기사
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.
-
기사
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.
-
기사
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.
-
기사
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.
-
고객 사례
Prison violence dramatically drops with analytics-based risk assessmentThe Indiana Department of Correction uses real-time data and predictive analytics from SAS to reduce violent attacks on staff by 50%.
-
고객 사례
Revolutionizing marketing campaigns with AIAlliant relies on machine learning to create qualified marketing audiences for its clients.
-
웨비나
Five AI Insights – And How Executives Can Use Them for Their AdvantageLearn insights, tips and proven practices from top leaders on the very front lines of the AI revolution.
-
기사
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.
-
고객 사례
항공기의 중요 임무를 지원하는 AI와 IoT 분석 기술Lockheed Martin revolutionizes aircraft maintenance with the SAS Platform.
-
기사
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.
-
기사
5가지 AI 기술인공 지능과 머신 러닝의 차이점을 알고 계십니까? 컴퓨터 비전이 일종의 AI 기술인 이유를 설명할 수 있습니까? 이 짤막한 설명서에서 그 해답을 확인해 보십시오.
-
기사
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.
-
기사
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.
-
기사
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.