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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e-Book
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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ホワイトペーパー
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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e-Book
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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e-Book
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◆アナリスト・〓レポート
IDC MarketScape: Worldwide Machine Learning Operations Platforms 2024 -
ホワイトペーパー
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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e-Book
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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e-Book
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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ホワイトペーパー
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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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.
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e-Book
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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e-Book
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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e-Book
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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〓分析◆アナリスト・〓レポート
IDC MarketScape: Worldwide Decision Intelligence 2024 -
〓分析◆アナリスト・〓レポート
ARC View: Industrial-grade AI: Transforming Data into Insights and OutcomesThis ARC View report explains how organizations can not only start realizing immediate returns from their Industrial AI initiatives, but also ensure that their investments remain future-proof.
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〓分析◆アナリスト・〓レポート
SAS is a Leader in The Forrester Wave™: AI / ML Platforms, Q3 2024 -
〓分析◆アナリスト・〓レポート
2024 Gartner® Magic Quadrant™ Data Science and Machine Learning -
e-Book
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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ホワイトペーパー
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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e-Book
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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ウェビナー
AI in Health Care: Enhance Clinical and Operational Decision MakingAI is revolutionizing the health care sector. Join SAS and Microsoft to explore innovative AI solutions for better patient outcomes and efficient care delivery.
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〓分析◆アナリスト・〓レポート
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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ホワイトペーパー
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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ホワイトペーパー
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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e-Book
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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e-Book
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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ホワイトペーパー
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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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.
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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?
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〓分析◆アナリスト・〓レポート
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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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.
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〓分析◆アナリスト・〓レポート
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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〓分析◆アナリスト・〓レポート
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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ユーザー事例
データ収集とモデリングの改善により、予測医学の取り組みを加速Dompé farmaceutici社は、予測分析（予測的アナリティクス）と定量的疾患モデリングのためにSASを活用しています。
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ユーザー事例
データを追加するだけ： データとテクノロジーは ── 人間味との組み合わせにより ── サステイナブルで質の高い料理体験をどのように生み出すのか？世界最大のパスタメーカーであるBarilla社は、高度なアナリティクスとAIを活用して全世界の在庫を追跡し、受注・配送を最適化することにより、急増する需要に対応しています。
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ユーザー事例
高度なアナリティクス、新しい税制措置の市民への影響を判断する政策立案者の取り組みに貢献ベルギーの財務当局は、検討中の税制改革案が生み出す “勝者” と “敗者” を、法規の制定前に確認しています。
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ホワイトペーパー
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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〓分析◆アナリスト・〓レポート
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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〓分析◆アナリスト・〓レポート
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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ホワイトペーパー
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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ホワイトペーパー
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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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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ホワイトペーパー
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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〓分析◆アナリスト・〓レポート
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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ユーザー事例
クラウドベースのアナリティクスとAIで顧客エンゲージメントを強化1-800-FLOWERS.COM社は、顧客の愛情表現、つながり合い、祝意伝達をSAS Viya on Azureで支援しています。
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ユーザー事例
フィンランド最大手のリテール銀行、顧客サービスとクレジット・スコアリングを改善するためにAIを適用S-Bankは、SAS Viya on Azureを活用して、より優れた顧客サービスと、より迅速かつ正確なローン契約処理を提供しています。
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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
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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記事
SASでデジタルトランスフォーメーションを加速し、迅速な意思決定を実現 -
記事
非構造化テキストに潜んでいる未利用のポテンシャルテキストは人間が生み出した最大のデータソースです。ソーシャルメディアへの投稿、チャットボットやデジタル・アシスタントとのやり取り、Eメールの送信、オンラインでのビジネス契約、レポートの生成などに伴い、また、コンピューターやモバイルデバイスを用いてその日の想いや活動を事実上 “ドキュメント化” する行為に伴い、その量は日々増大しています。
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記事
チャットボットとは？チャットボットとは、人間とコンピューターのやり取りを簡素化するために設計された会話型AIの一種です。この記事では、チャットボットがビジネスでどのように利用されているか、また、チャットボットをアナリティクス・アプリケーションにどのように組み込めるかを説明します。
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記事
ModelOps： モデル・ライフサイクルを業務運用化する方法ModelOpsとは、分析モデルがデータサイエンス・チームからIT本稼働チームへと所定のサイクルに沿って受け渡され、一定のリズムでデプロイ（業務実装）および更新されるようにするための手法です。ModelOpsは、AIモデルから価値を創出する競争において、ごく少数の企業だけが利用している勝利要因です。
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〓分析◆アナリスト・〓レポート
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◆アナリスト・〓レポート
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◆アナリスト・〓レポート
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◆アナリスト・〓レポート
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◆アナリスト・〓レポート
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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記事
Digital Transformation in SMBSAS® Viya®は、一つの環境でアナリティクスに必要な機能を全て実現したクラウド対応のプラットフォームです。アジャイルなIT環境に欠かせない高い信頼性、スケーラビリティ、セキュリティを備えたアナリティクス環境とガバナンスを提供することにより、 データ・サイエンティストからビジネス・アナリスト、アプリケーション開発者、そして経営幹部まで、あらゆる人々のニーズに対応します。
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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
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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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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ホワイトペーパー
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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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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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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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.
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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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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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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.
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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.
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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.
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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.
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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.
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ホワイトペーパー
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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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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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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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
TDWI Checklist Report Six Best Practices to Ignite the Customer Experience with IoTcustomer data, IoT
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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
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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ホワイトペーパー
Advanced Analytics: Moving Toward AI, Machine Learning, and Natural Language Processingadvanced analytics, artificial intelligence, machine learning, natural language processing
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ホワイトペーパー
TDWI Navigator Report: Predictive AnalyticsPredictive Analytics
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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.
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ホワイトペーパー
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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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.
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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.
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記事
AIマーケティング： どのような未来を秘めているのか？AIマーケティングとは、人工知能（AI）とアナリティクスを活用してリアルタイム・パーソナライゼーションでカスタマー・エクスペリエンスを強化しながら、マーケティング結果の改善を図る取り組みのことです。
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〓分析◆アナリスト・〓レポート
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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記事
大和証券の成約率を2.7倍にしたAI×マーケティング膨大な個人顧客と多種多様な商品、顧客接点を持つリテールビジネスにおいて、その都度「次の最善な一手」を導き出し続けるのは容易ではない。営業担当者の「経験」や「勘」だけに頼れば、結果的に顧客に提供するサービスの質にもバラつきが発生しかねない。大和証券ではこうした課題を解決し顧客満足度を向上させるために、AI技術を導入した。
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〓分析◆アナリスト・〓レポート
Gartner positions SAS as a Leader in the Magic Quadrant for Data Science and Machine Learning Platforms, Q1 2021Gartner positions SAS as a Leader in the Magic Quadrant for Data Science and Machine Learning Platforms for the eighth consecutive year.
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ユーザー事例
Smart city uses analytics and IoT to predict and manage flood eventsThe Town of Cary, NC teams up with SAS and Microsoft to protect citizens from flooding, safeguard watersheds and support environmentally sound development.
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記事
サプライチェーンの成功のためにAIと機械学習を活用する方法 -
ユーザー事例
AIでマーケティング・キャンペーンを革命Alliant社は、機械学習を活用して顧客企業向けに有望なマーケティング対象者データを生成しています。
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ユーザー事例
人工知能（AI）とIoTアナリティクス、重要なミッションを担う航空機の運行維持に貢献Lockheed Martin社は、SAS Platformで航空機の保守整備を革命的に改善しています。
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記事
オープンなAIプラットフォーム - SAS ViyaSAS® Viya®は、一つの環境でアナリティクスに必要な機能を全て実現したクラウド対応のプラットフォームです。アジャイルなIT環境に欠かせない高い信頼性、スケーラビリティ、セキュリティを備えたアナリティクス環境とガバナンスを提供することにより、 データ・サイエンティストからビジネス・アナリスト、アプリケーション開発者、そして経営幹部まで、あらゆる人々のニーズに対応します。
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ユーザー事例
IoTデータと人工知能（AI）の融合が稼働停止時間を削減し、追跡管理の向上にも効果を発揮Volvo Trucks社とMack Trucks社では、センサーデータとSASのAIソリューションを活用して、画外の稼働停止時間を最小化しています。
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記事
5大AIテクノロジー人工知能（AI）と機械学習の違いをご存知でしょうか？また、コンピューター・ビジョンがAIテクノロジーの下位分野である理由を説明できるでしょうか？その答えは、この簡潔な説明の中で見つかります。
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ユーザー事例
Finding your best customers with machine learningSeacoast Bank enhances customer value using AI and SAS Visual Analytics on SAS Viya.
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記事
すばらしい新世界における機械学習と人工知能What is the interplay between man and machine in a brave new world with AI?
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記事
参加無料型ネットゲームが大きな利益を生む理由参加無料型のMMO（多人数参加型オンライン）ゲームのリーダー企業であるWargaming社は、SASの工業化されたモデリング環境をどのように活用して顧客のニーズに応えているのでしょうか？
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ブログ記事
機械学習のパラメータをオートチューニング機械学習で予測モデルを作るとき、課題のひとつにパラメータのチューニングがあります。このチューニングを自動で行ってくれる夢のような機能が、SAS Viya のオートチューニングです。
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ブログ記事
人工知能：ブームと現実を切り分けて認識するためにAIは “機械に更なるスマート性を” 組み込むために役立っていますが、世界を征服しつつあるわけではありません。私たちはAIに何を期待すべきでしょうか？
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ブログ記事
機械学習アルゴリズム選択ガイド機械学習に取り組み始めた時にまず感じる疑問は「どのアルゴリズムを使えばよいのか？」でしょう。機械学習アルゴリズムには多くの種類があり、そのすべてを熟知している人以外は、なかなかすぐに最適なアルゴリズムを選択できません。ここでは、目的に最適なアルゴリズムを見つけ出すためのチートシートを紹介します。
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記事
持続可能なGDPRコンプライアンス体制の実現に向けた5つのステップ本稿で説明するステップに従えば、2018年5月の発効日までにGDPRコンプライアンスを達成した上で、追加のメリットも実現することができます。
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記事
IoTデータへの機械学習の適用機械学習やモノのインターネット（IoT）に関する理論的な議論から離れ、実用的なビジネス・アプリケーションについてお話しします。
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記事
機械学習入門：よくある5つの誤解（英語）データセットの巨大化と複雑化が進むなか、機械学習（マシン・ラーニング）への注目度が高まっています。これはどのような仕組みなのでしょうか？ キンバリー・ネバラが、5つのよくある誤解を解きながら機械学習とは何かを説明します。
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記事
パーソナル・データ・サイエンティストの可能性についてSiriに天気を尋ねるのと同じ感覚で、デスク上のボタンを押して最新の販売予測を確認できるとしたら？ 本稿ではパーソナル・データ・サイエンティストの可能性を探ります。
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記事
ジカウイルスの阻止： ビッグデータとアナリティクスの可能性アナリティクスの専門家、現地の医療機関、米疾病対策予防センター（CDC）の学術研究コミュニティ、ワクチンメーカーが一致団結すれば、ジカウイルスの蔓延を阻止できるはずです。
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.