Find out how analytics, from data mining to cognitive computing, is changing the way we do business
A business glossary improves data quality – one of the top five ways it makes analytics better.
Find out how analytics, from data mining to cognitive computing, is changing the way we do business
A business glossary improves data quality – one of the top five ways it makes analytics better.
Los datos, y sobre todo su significado y usabilidad, se han ido transformando con el tiempo. Anteriormente hablar de datos era pensar en unos y ceros, en tablas estáticas o incluso en materiales que no se aprovechaban. Hoy, pensar en datos es pensar en la fuente principal de las historias,
What is an efficient way to evaluate a multivariate quadratic polynomial in p variables? The answer is to use matrix computations! A multivariate quadratic polynomial can be written as the sum of a purely quadratic term (degree 2), a purely linear term (degree 1), and a constant term (degree 0).
“Ocean acidification is sometimes referred to as global warming's equally evil twin.” ~ Elizabeth Kolbert This is the second post in my two-part series about climate change. You can read part 1 of this series here. When engaging in data exploration for insights, it’s good practice to start with a
The dsAutoMl action is all that and a bag of chips! In this blog, we took over all aspects of the data science workflow using just one action.
Colleges and universities have access to enormous stores of data and analytics has the power to help higher education tackle some of its biggest challenges. Larry Burns, Assistant Director of Institutional Research and Information Management (IRIM), Oklahoma State University (OSU) knows a great deal about the power of analytics to
In a linear regression model, the predicted values are on the same scale as the response variable. You can plot the observed and predicted responses to visualize how well the model agrees with the data, However, for generalized linear models, there is a potential source of confusion. Recall that a
앞으로 10년 뒤, 2030년에는 어떤 브랜드가 살아남아 성장을 지속할 수 있을까요? SAS와 글로벌 시장조사기관 퓨처럼 리서치(Futurum Research)는 SAS 애널리틱스 익스피리언스 2019에서 ‘2030년 고객 경험의 미래(Experience 2030: The Future of Customer Experience)’ 설문조사 보고서를 발표했습니다. 다니엘 뉴먼(Daniel Newman) 퓨처럼 리서치 수석분석가 겸 창립 파트너는 더 많은 권한을 갖게 된(empowered) 소비자가 새롭게
지난 10월 21일부터 23일까지 이탈리아 밀라노에서 열린 'SAS 애널리틱스 익스피리언스 2019(SAS Analytics Experience 2019)'에서는 SAS의 머신러닝, 컴퓨터 비전, 자연어처리 등 AI 기술을 기반으로 기업들이 어떻게 실제(real) 가치를 실현할 수 있는지 보여주는 다양한 사례들이 소개되었습니다. 특히 행사 둘째 날에는 짐 굿나잇 SAS CEO, 올리버 샤벤버거 SAS 수석부회장 겸 최고운영책임자(COO) & 최고기술책임자(CTO)의
*Post basado en la presentación de Isabel Cristina Zuluaga de Tuya en SAS Forum Colombia Cada año en Colombia, cerca de 1,5 millones de personas inician su vida crediticia y obtienen su primer puntaje de riesgo (según cifras de la Superintendencia Financiera de Colombia). Los recién llegados al sistema buscan
지난 10월 21일부터 23일까지 이탈리아 혁신 기술의 중심지 밀라노에서는 유럽 최대 규모의 분석 컨퍼런스 ‘SAS 애널리틱스 익스피리언스 2019(SAS Analytics Experience 2019)’가 개최됐습니다. 3일간 밀라노 컨벤션 센터(Mico Milano Convention Centre)에서 진행된 올해 컨퍼런스에는 1,800명이 넘는 데이터 사이언티스트와 비즈니스 리더들이 모여 다양한 논의가 진행되었으며, 참석자들에게는 56개의 breakout 세션, 48개의 데모 부스, 그
Getting value from analytics is becoming top of mind for businesses. Organizations have invested millions of dollars in data, people and technology and are looking for a return on their investment. That requires operationalizing analytics so that it can be used for strategic decision making -- often referred to as
Ladies and gentlemen, I give you Value-Based Payments (VBP), health care’s new magic, “silver bullet” that will solve all our fraud problems. Last month, the US Department of Health and Human Services (HHS) issued a press release entitled, “HHS Proposes Stark Law and Anti-Kickback Statute Reforms to Support Value-Based and
“The future is already here — it's just not very evenly distributed.” ~ William Gibson, author The same can be said for climate change – global warming is here, in a big way, but its effects are still an arm's length away for many of us. How is climate change
Biplots are two-dimensional plots that help to visualize relationships in high dimensional data. A previous article discusses how to interpret biplots for continuous variables. The biplot projects observations and variables onto the span of the first two principal components. The observations are plotted as markers; the variables are plotted as
A major UK insurance company used text analytics to categorise complaints.
US military veterans are mission-focused, team-oriented and natural leaders that benefit any organization that hires them. Many of today's veterans organizations use data and analytics to help transition military members and their spouses find rewarding civilian careers. SAS supports those efforts and we're also proud to offer many programs to
I recently saw in several social media posts that sales of vinyl records are forecast to be higher than sales of CDs this year (2019) for the first time since 1986. Two questions came to mind - 1) Is this true? and 2) Is this a big deal? Let's analyze
Are you looking for a Data Science easy button? The dataSciencePilot action set comes pretty close.
Principal component analysis (PCA) is an important tool for understanding relationships in continuous multivariate data. When the first two principal components (PCs) explain a significant portion of the variance in the data, you can visualize the data by projecting the observations onto the span of the first two PCs. In
Think differently about using storage in the cloud with your SAS Grid jobs, and learn about SAS Cloud Data Exchange for security/caching strategies
According to the Price Waterhouse Cooper 2018 Global Economic Crime and Fraud Survey, the reported rate of economic crime is on the rise, up to 49% in 2018. That makes the use case I want to share particularly relevant, no matter what industry or sector you're in. This use case
Understanding multivariate statistics requires mastery of high-dimensional geometry and concepts in linear algebra such as matrix factorizations, basis vectors, and linear subspaces. Graphs can help to summarize what a multivariate analysis is telling us about the data. This article looks at four graphs that are often part of a principal
When I started working in data and analytics 30 years ago, information security wasn’t high on the agenda for organizations. That's changed with the rise of the Internet, and now that cloud is becoming more and more prevalent in organizations, information security is no longer just the domain of specialists
Was haben SAS Viya und die österreichischen Berge gemeinsam? Eine ganze Menge! Neulich besuchten mich Freunde aus Tirol am Neusiedler See, also im Burgenland. Bekanntermaßen ist Tirol ein Bundesland im Hochgebirge. Entsprechend amüsiert waren meine Freunde, als ich ihnen den Rosenberg und den Ungerberg in der Nachbarschaft zeigte. „Bei uns
I suffer from arthritis. You can tell just by watching me walk: Depending on the day, I have a slight limp, which varies in severity based on a number of factors such as the time of day and recent physical activity. Years of treatment for my condition have shown me
本シリーズの記事について オープンソースとの統合性はSAS Viyaの一つの重要な製品理念です。SAS言語やGUIだけではなく、R言語やPythonなどのオープンソース言語でも、SAS ViyaのAI&アナリティクス機能を活用することが可能になっています。このシリーズの記事は、R言語からSAS Viyaの機能を活用して、データ準備からモデルの実装までの一連のアナリティクス・ライフサイクル開発をサンプルコードの形で紹介していきます。 CASサーバーとSWATパッケージとは コードの内容を紹介する前に、まずCASサーバーとSWATパッケージに関して、簡単に紹介します。CASはSAS Cloud Analytic Serviceの略称です。SAS Viyaプラットフォームの分析エンジンで、様々な種類のデータソースからデータを読み込み、メモリーにロードし、マルチスレッドかつ分散並列でハイパフォーマンスな分析処理を実行します。現在のCASサーバーは3.4.0以降のバージョンのPythonと3.1.0以降のバージョンのRをサポートしています。 オープンソース言語のクライアントからCASサーバーのインタフェースを使用するために、SASからSWAT(SAS Scripting Wrapper for Analytics Transfer)というパッケージをGithubに公開し、提供しています。RとPythonにそれぞれ対応しているバージョンはありますが、本記事のサンプルコードではR用の SWATをメインで使用します。SWATパッケージを通してCASサーバーと通信し、インタフェースを直接利用することができます。データサイエンティストはSWATパッケージを使用し、RやPythonからSAS Viyaの豊富なAI&アナリティクス機能を活用し、様々なデータ分析処理を行ったり、機械学習や深層学習のモデルを作成したりすることができます。 環境の準備 R言語用SWATパッケージを利用するために必要なRの環境情報は以下の通りです。 ・64-bit版のLinux或いは64-bit版のWindows ・バージョン3.1.0以降の64-bit版のR ・Rパッケージ「dplyr」、「httr」と「jsonlite」がインストールされていること 筆者が使用している環境は64-bit版のWindows 10と64-bit版のR 3.5.3となり、IDEはRstudioです。 パッケージのインストール SWATをインストールするために、標準的なRインストール用関数install.package()を使用します。SWATはGithub上のリリースリストからダウンロードできます。 ダウンロードした後、下記のようなコマンドでSWATをインストールします。 R CMD INSTALL R-swat-X.X.X-platform.tar.gz X.X.Xはバージョン番号であり、platformは使用するプラットフォームと指しています。 或いはRの中から下記のコマンドのようにURLで直接インストールするのもできます。 install.packages('https://github.com/sassoftware/R-swat/releases/download/vX.X.X/R-swat-X.X.X-platform.tar.gz', repos=NULL, type='file') この部分の詳細はR-swatのGitHubのリンクを参考にしてください。 SAS Viyaと一回目の通信をやってみよう 全ての準備作業が完了したら、問題がないことを確認するために、Rから下記のコードを実行してみます。 library("swat") conn <- CAS(server, port, username, password,
If you're looking for advice on developing an analytics strategy, there's no shortage of resources, including this from SAS: Building your data and analytics strategy. If, on the other hand, you're looking for advice on how to apply analytics to strategic planning, your search has likely to come up wanting.
Data-driven businesses use technology as an insight platform to empower nontechnical users.
“Analytics Can Save Higher Education. Really.” is a call to action for the higher education community to leverage data and analytics for better decision making at colleges and universities. It stresses the importance of using data and analytics to improve student outcomes, campus operations and much more. Oklahoma State University