A intensidade do choque sobre a economia mundial em decorrência da pandemia do COVID-19 ainda precisa ser determinada. Conforme os negócios desenvolvem, seus próprios entendimentos sobre como eles podem ser afetados, dois elementos constantes em todas as avaliações são incertezas e complexidade. O futuro depende de diversos fatores, incluindo políticas
Digitalization, big data and AI are changing the role of insurance and, therefore, the role of actuaries. A lot of reports – like McKinsey’s Insurance 2030, Deloitte’s “The Exponential Actuary," or the Big Data and Insurance report by the Geneva Association (a leading think tank of insurance CEOs) depict aspects
Learn how SAS and Microsoft aim to meet FinServ’s evolving analytics demands through a new strategic partnership.
Many textbooks and research papers present formulas that involve recurrence relations. Familiar examples include: The factorial function: Set Fact(0)=1 and define Fact(n) = n*Fact(n-1) for n > 0. The Fibonacci numbers: Set Fib(0)=1 and Fib(1)=1 and define Fib(n) = Fib(n-1) + Fib(n-2) for n > 1. The binomial coefficients (combinations
기업이 데이터 기반의 의사결정을 하기 위해서는 AI를 특정 영역이 아닌 분석 라이프사이클 전반으로 확대하고, 이 라이프 사이클은 의사결정 프로세스와 연결돼야 합니다. 개방된 플랫폼에서 분석 시간을 줄이고, 그 결과를 운영시스템에 빠르게 적용해 더 큰 비즈니스 가치를 실현할 수 있어야 합니다. 지난 시리즈에서는 모델링 작업을 위한 피처 자동 생산과 자동 튜닝 정도로
Five years ago, 193 countries joined forces and formed the United Nation’s Sustainable Development Goals. These goals, which are commonly referred to as the Global Goals, serve as a universal promise—an ambitious pledge to build a better future for people and planet by 2030. This year marks the final 10-year
We will combine three separate SAS Viya capabilities to create an application that can manage multiple models, interpret model outputs, and replace the production model if necessary
Innovation is currently an extremely desirable feature for every country. However, a ranking published by the European Commission shows that Poland is struggling to create an environment that supports development. Development and innovation need people with competence in new technologies, such as analytics. Last year’s Modelling for Business conference showed
Mit Hans-Peter Zorn, AI-Influencer und Praktiker, im AI Talk.
What analytics architecture is needed to support an accelerator? I have recently been working with my colleague Jussi Martikka to extract lessons from the City of Helsinki’s AI Experimentation Accelerator work. We used the steps of the accelerator process to define the analytics architecture needed. This was a useful way
A previous article discussed how to solve regression problems in which the parameters are constrained to be a specified constant (such as B1 = 1) or are restricted to obey a linear equation such as B4 = –2*B2. In SAS, you can use the RESTRICT statement in PROC REG to
The practice of business forecasting falls well short of the potential exhibited in academic research and forecasting competitions. Chris Chatfield* noted this in a 1986 editorial in the International Journal of Forecasting, where he called on statisticians to find a better way of communicating the better use of existing methods
Je m’appelle Franck. Je suis consultant. Depuis 2003, j’accompagne de grands établissements pour renforcer leurs dispositifs de lutte contre le blanchiment (AML) et le financement du terrorisme en déployant des progiciels. 17 ans sont passés, ils fonctionnent toujours. Problème : ils sont devenus des monstres ! Je prends conscience de
SAS Japanでは”Data for Good”を目指す学生コミュニティ「SAS Japan Student Data for Good community」を運営しています。このコミュニティは、Data For Goodを題材にデータサイエンスの一連の流れを体験する場として設立されました。今回紹介する勉強会も、その活動の一環です。詳しくは「Data for Goodを通じて"本物の"データサイエンティストになろう！」の記事をご覧ください。活動の様子についてはFacebookにて共有していますので、そちらもご参考にしてください。 五回目の勉強会では海洋汚染をテーマに、Data for Goodの活用事例から課題設定の部分を学びました。また、今回は初めてオンラインでの開催をしましたので、その様子もお伝えしたいと思います。 海洋保護に向けたD4Gの取り組み/マイクロプラスチック問題 SDGsの一つに“海の豊かさを守ろう(LIFE BELOW WATER)”という項目があります。日本でも2020年7月からスーパーやコンビニエンスストアにてレジ袋の有料化が始まりました。その背景の一つにはマイクロプラスチック問題があります。コミュニティのメンバーがこのテーマでData for Goodに取り組んでいるので、今回はその活動について共有しました。 マイクロプラスチック問題とは、特に海洋環境において微小なプラスチック粒子が海洋生物に対し悪影響を及ぼしてしまうことです。また生物濃縮により海洋生物だけでなく、人間にも間接的に影響があります。レジ袋の有料化や製品へのスクラブ等使用の規制の動きが世界的に進んでいます。環境保全にいち早く取り組んでいる海外の先進諸国のデータをもとに、今後日本にも導入するべき取り組み、推進していくべき取り組みを明確にしようというのが今回の活動目的になります。 今回の勉強会の活動紹介では、この問題の現状と最新の研究、既に行われている取り組みの効果検証について取り上げました。意思決定の場に置いて、ある施策が目的とするものに対して効果があるのかどうかは非常に重要です。特にマイクロプラスチック問題のように規模が大きい問題に対してはその効果の大きさだけでなく、費用対効果にも注目しなければなりません。しかし、効果の推定には比較実験が必要になりますが多くの場合それは存在しないため、自然実験という考え方を用いてアプローチしていきます。 詳細については今後このブログの中でご紹介していきます。 海洋プラスチック汚染問題をデータで解決する 今回は、コミュニティーメンバーがテーマとして活動している「海洋汚染」に関連して、オランダに拠点を置く非営利のエンジニアリング環境団体 The Ocean Cleanupの事例を紹介しました。 The Ocean Cleanupは、太平洋で無人のゴミ回収装置であるクリーンアップシステムを開発しています。その運用においてある課題が浮かび上がりました。太平洋には多くのプラスチックが集まっているとされる「太平洋ゴミベルト」と呼ばれるエリアがありますが、その範囲は非常に広大かつ陸地から遙か遠くにあります。システムを運用する費用を考慮して、効率的にゴミを回収するにはどうすればよいでしょうか。この課題に対して、The Ocean Cleanupではビッグデータを用いて太平洋ゴミベルトの可視化を行いました。 調査団はこれまでの海洋研究の知見とともに、独自に大規模な調査を行いました。太平洋ゴミベルトのサイズ・位置・プラスチックの量・プラスチックの分布と4つの可視化の観点などから進められてきました。 プラスチック汚染は複雑で大規模な問題であるため、包括的で大掛かりな解決策が必要となります。そのため、データサイエンスの活用によって、問題を理解し効率よく解決するための知見が得られます。クリーンアップシステムでは、監視カメラや衛星との交信による位置情報から実際のシステムの動きや回収度を確かめることができます。ビックデータによる分析結果だけでなく、実際のパフォーマンスデータから得られた知見からより良いシステムの構築が現在も行われ続けています。 以上の話を踏まえて、最後に参加者同士でディスカッションを行いました。自分たちの生活と繋げて考えたり、事例の中で興味深かった点についてお互いに話すことが出来ました。また、海洋保護をテーマに今後活動していく上で考えるべき点についても触れながら議論を進められ、有意義な時間になりました。 今回は初めてのオンライン開催でしたが、オンラインであることの良さを活かして定期的に勉強会を企画するとともに、次回から更に質の高い勉強会をつくっていきたいと思います！ コミュニティメンバー募集中！ SAS Japan Student Data for Good
Getting people with mental health conditions the help they need is a top priority for many Californians, according to a recent California Health Care Foundation report. In 2004, Golden State voters approved the Mental Health Services Act (MHSA). Enacted into law in January 2005, MHSA has generated approximately $15 billion
In the third post of his series, Jim Harris looks at types, terms and timing of coronavirus tests.
Whenever I talk to actuaries across EMEA, they are very consistent in the many anchor points they see for actuarial modernization in order to be future-proof. In this article, I would like to share some of them. Anchor points for actuarial innovation The most time-consuming task is, of course, getting
I recently sat down with Colin Wright, Global Solutions Director of Retail & Consumer Goods at Microsoft, to explore the opportunities that SAS and Microsoft’s new strategic partnership creates for retailers around the world. Retailers are awakening to the fact that the near limitless scale and compute power of the
최근 SAS는 클라우드에서 AI와 분석의 미래를 더욱 구체화하기 위해 마이크로소프트와 새로운 전략적 파트너십을 체결했습니다. 이번 파트너십으로 SAS 고객은 클라우드 환경에서 훨씬 수월하게 분석을 수행할 수 있습니다. 또한 SAS의 AI 및 분석 솔루션과 마이크로소프트 애저(Azure)의 긴밀한 통합으로 수백만 명의 애저 고객은 SAS 기술을 편리하게 활용하여 분석 성능을 한층 개선할 수 있습니다.
A data analyst recently asked a question about restricted least square regression in SAS. Recall that a restricted regression puts linear constraints on the coefficients in the model. Examples include forcing a coefficient to be 1 or forcing two coefficients to equal each other. Each of these problems can be
The popular image of data scientists is very much a bit of a geek or nerd. However, that’s not strictly accurate. It may not be – as Harvard Business Review famously suggested – the sexiest job of the 21st century. But it is a long way from the perceived world
A note from Udo Sglavo: In Digital transformation, scientific computing, and peace of mind, I mention that the COVID-19 pandemic is paralyzing the world. However, new challenges are also inspiring new ideas to tackle those challenges. We might ask questions about what is causal in nature, trying to figure out
Claudia Kleinert, die Frau von den ARD Wetternews, im Gedankenaustausch.
My 2020 SAS Global Forum paper was about how to write custom parallel programs by using the iml action in SAS Viya 3.5. My conference presentation was canceled because of the coronavirus pandemic, but I recently recorded a 15-minute video that summarizes the main ideas in the paper. One of
The Text Investigation Framework utilizes several technologies built on SAS Viya, including SAS Visual Text Analytics, SAS Visual Data Mining and Machine Learning, and SAS Visual Investigator. SAS Visual Investigator acts as the orchestrator to surface the results. With its broad set of capabilities, SAS Visual Investigator can perform scenario authoring, alert generation and disposition, and comprehensive workflow to gather vital outcomes and feedback.
To get 100% right at a test is something that does not happen every day. But it is achievable. There are different ways of getting a high score and here is one example. Laurent Barmaverain - a business intelligence and data science master's degree student at the university of Turin,
After a day out shoveling snow from a freak early September storm, here is editor-in-chief Len Tashman's preview of the Fall 2020 issue of Foresight: The International Journal of Applied Forecasting. Preview of Foresight (Fall 2020) The Fall 2020 issue of Foresight—number 59 since inception in 2005—features the final installment of
The pandemic may have other implications for manufacturing. For example, we could see factories moving away from a reliance on physical labour.
Congratulations to Rick Wicklin for 10 Years of The Do Loop Rick Wicklin, author of The Do Loop I want to take a moment to congratulate my colleague Rick Wicklin on the 10th Anniversary of his blog, The Do Loop. Rick is Distinguished Researcher in Computational Statistics at SAS, and our
I previously wrote about the RAS algorithm, which is a simple algorithm that performs matrix balancing. Matrix balancing refers to adjusting the cells of a frequency table to match known values of the row and column sums. Ideally, the balanced matrix will reflect the structural relationships in the original matrix.
