Here at SAS, we understand the importance of having access to cutting-edge professional resources. That’s why, for more than 40 years, we’ve provided individuals in programming, data management and analytics fields with low-cost and no-cost materials that promote success in their educational and professional journeys. And today, as the demand
Tag: SAS Visual Analytics
Data visualization is a critical way for anyone to turn endless rows of data into easy-to-understand results through dynamic and understandable visuals. Whether your favorite visualization is a pie chart, a geographic map, or relies on natural language, showing the insights that empower you to make more informed decisions is a better way to do data-driven business. Analyst firms say that SAS has market-leading data visualization. This helps users across the globe find insights in their data using new and exciting trends in data visualization.
Have you ever heard something referred to as the bee’s knees? Most likely the person uttering that expression meant that it was truly amazing and extraordinary. Maybe you stopped and pondered the origin of the phrase. Well wonder no more! In the 1920s in the United States, people were obsessed
When we moved out to the country with our two dogs, our oldest dog Todd suddenly decided he liked to howl…. And he would do so every time we left the house. Maybe it was the country air? Maybe it was a time-lapse gene? Maybe he just wanted to learn
지난 블로그 포스팅 #1편에서는 임상시험 전 과정에 참여한 내.외부 모든 이해관계자가 임상시험 데이터에 쉽게 접근하여 진행 상황을 파악할 수 있도록 지원하는 SAS Visual Analytics 솔루션의 기능을 소개해 드렸습니다. 이번 포스팅에서는 이러한 AI기반의 SAS Visual Analytics 분석 솔루션을 활용하여 임상시험 SDTM 데이터의 탐색 및 시각화 리포트의 활용에 대해 알아보겠습니다. Clinical Data
임상시험을 비롯한 모든 업무에서 분석은 필수이며, 점점 고급분석을 필요로하고 있습니다. 이번 블로그 포스팅은 2편으로 나누어 1편에서는 임상시험 전 과정에 참여한 내.외부 모든 이해관계자가 임상시험 데이터에 쉽게 접근하여 진행 상황을 파악할 수 있도록 지원하는 SAS Visual Analytics 솔루션의 기능을 소개합니다. 이어 2편에서는 임상시험의 SDTM 데이터를 활용하여 SAS Visual Analytics 솔루션에 어떻게
学生の皆さんは今日から冬休みでしょうか。「卒論でそれどころじゃないよ！」という方もいるかもしれませんが、この期間に「何か新しい勉強を始めてみようかな」と思われる方も多いのではないでしょうか。 データサイエンティストが「21世紀で最もセクシーな仕事」と言われてから10年近くが経とうとしています。しかし、社会におけるデータの活用はまだまだ発展途上であり、そのための人材は依然として高い需要があります。「データサイエンティスト」はそのなかでも、多くの高度な知識と技能を持った人材ですが、デジタル・トランスフォーメーション（DX）と呼ばれる業務改革が進む中、高度人材だけでなく、より広範囲の人たちがデータを活用した仕事に従事することが求められています。数理科学とテクノロジーを駆使するデータサイエンティストでなくても、アナリティクスに関わり、自分なりの知識とスキルを発揮することができます。 SAS Skill Builder for Students は、SASソフトウェアと統計解析・機械学習を中心に、「データリテラシー」や「ビジュアライゼーション」といったより基礎的なの知識やスキルを無料で学習できます。また、認定資格取得の案内や、アナリティクスを活用したキャリアについての情報も提供しており、アナリティクスの初学者からデータサイエンティストのキャリアを構築しようとする学生まで、多くの方に活用いただけます。この機会にぜひ登録してください。 登録方法は次の4ステップ SAS Skill Builder for Students にアクセス SASプロファイルをお持ちでない学生は「SAS プロファイルを新規に登録」から登録 ※ 登録するメールアドレスは大学ドメイン（.ac.jpなど）のものを入力してください。 登録したSASプロファイルのメールアドレスを SAS Skill Builder for Students のログイン画面で入力 My Trainingの画面でLicense Agreementを読み、同意のチェックボックスにチェックを入れて「Submit」 登録・ログインに成功するとこちらのようなホーム画面が表示されます。 「Learn SAS」「Get SAS Certified」「Career Resources」のタブがあり、それぞれe-Learningによる学習、認定資格の案内、キャリア構築のためのリソースが提供されています。 ここでは「ビジュアライゼーション」のe-Learningをご紹介します。SAS Visual AnalyticsというGUI操作による可視化ツールを利用して、データから示唆を得る方法を学習するトレーニングです。数学やプログラミングが苦手な方でも学習できます。 「Learn SAS」タブ→「Start Learning」→「Visual Analytics and Visual Statistics」→「SAS Visual Analytics 1 for SAS
Active gratitude is the feeling you get when a stranger does something nice for you without expecting anything in return. While both are beneficial for our health, there is a statistically significant, positive correlation between active gratitude and pro-sociality (r = 0.374), that is not present with passive gratitude. In other words, random acts of kindness trigger other random acts of kindness to other people, which is both good for us and good for society.
SAS' Cindy Wang uses SAS Visual Analytics to explore how people around the world spend their days.
SAS' Bahar Biller, an operations researcher, details how to develop a supply chain digital twin.
Technological advancements in connectivity and global positioning systems (GPS) have led to increased data tracking and related business use cases to analyze such movements. Whether analyzing a vehicle, an animal or a population's movements - each use case requires analyzing underlying spatial information. Global challenges such as virus outbreaks, deforestation
It’s safe to say that SAS Global Forum is a conference designed for users, by users. As your conference chair, I am excited by this year’s top-notch user sessions. More than 150 sessions are available, many by SAS users just like you. Wherever you work or whatever you do, you’ll
Cindy Wang's curiosity about the Mandelbrot set led her to draw one using SAS Visual Analytics.
SAS Global Forum 2021 will be jam-packed with inspiring content. Register today to ensure you don't miss a second of this year's event.
Readers of my earlier post Discover Visual Analytics Report Paths with REST APIs asked for ways to export SAS Visual Analytics (VA) report content programmatically. I know this is a topic of interest from many VA report designers. So, I think it’s better to write something on this and I
The people, the energy, the quality of the content, the demos, the networking opportunities…whew, all of these things combine to make SAS Global Forum great every year. And that is no exception this year. Preparations are in full swing for an unforgettable conference. I hope you’ve seen the notifications that
Find out the most popular SAS Users YouTube channel how to tutorials, and learn a thing or two!
In recent years, we have seen some astronomical contracts given to professional athletes. Major League Baseball (MLB) has certainly had its share. One of its first notable “megadeals” was when Alex Rodriguez, the Seattle Mariners’ power-hitting shortstop, left the team to join the Texas Rangers in 2001. The Rangers committed
If you’re like me and the rest of the conference team, you’ve probably attended more virtual events this year than you ever thought possible. You can see the general evolution of virtual events by watching the early ones from April or May and compare them to the recent ones. We
Conversational AI can offer a way to provide that always-on 24/7, fast, convenient experience that can go anywhere (phone, computer smart speakers, even your car). It can provide a human-like experience through real-time, personalized interaction with AI running in the background. This technology is being applied across many industries for a variety of use cases (both customer-facing and for internal use).
Public and private schools are struggling to figure out how to bring face-to-face instruction to students during this pandemic. Health risks to students and teachers, parents struggling with child-care options and/or support for virtual learning, and schools’ capacities and budget limitations make this problem a severe logistical challenge. Schools need
[Editor's note: This post was co-authored with Fritz Lehman, COO of Zencos] In 1976, the blockbuster movie Jaws was the number one grossing film. Why? Because it had a great villain – the great white shark. The movie told a vivid (and all too familiar) story about plans gone awry
Discovery is an important part of setting up your analysis for success – essentially it prevents you from plunging into a haystack to try to find that elusive needle, and rather, helps you organize the haystack into neater, compact organized bales that you can navigate with ease. Proper discovery can help you more efficiently find patterns in your data set.
Everyone knows that SAS has been helping programmers and coders build complex machine learning models and solve complex business problems for many years, but did you know that you can also now build machines learning models without a single line of code using SAS Viya? SAS has been helping programmers
[Nabaruna Karmakar was coauthor of this post] A study was conducted at the University of Denver on The Economic Impacts of the Austin, Texas "No Kill" Resolution. The study found great value in creating an animal welfare-focused community. It highlighted the benefits of economic growth due to an increased need in
Unlocking the potential of your unstructured text data can lead to great business outcomes but the prospect of starting a new or enhancing your existing Natural Language Processing (NLP) program can feel overwhelming because of the inherently unique (and sometimes messy) nature of human language. Text data doesn’t fit neatly into rows or columns the way that structured data does, which can make it seem more complex to work with. Conversations and written language range from objective statements to subjective perspectives and opinions. The same sentence, depending on its intent and the nuances in how it's said, can have a positive, negative, or neutral sentiment. To get us started, we'll share different types of NLP models used to analyze unstructured data with a focus on the hybrid approach.