En un mercado con clientes cada vez más exigentes, la experiencia del cliente se ha convertido en un factor decisivo. En este contexto, la IA generativa emerge como un aliado estratégico, transformando la gestión de la experiencia del cliente y fortaleciendo la relación con ellos. Desde conversaciones automatizadas hasta la
It is unfortunate, but the procurement process is rife with the potential for loss, waste, abuse, and fraud. It requires many different steps to be performed by different departments, including ethics and compliance, audit, procurement, and fraud investigation. Procurement has also been somewhat slower to develop and adopt the kind
In statistical tables in SAS, a dot (.) represents a numerical missing value. Although a dot is the default symbol in SAS, other languages use other symbols. The R language prints the symbol NA, which stands for "not available." The MATLAB language uses NaN ("Not a Number"). In Python, many
SAS has a programming language, but IS that all it is? Nope, but it still ranks high as a most marketable programming skill.
Data and AI literacy are no longer optional but essential for success in both academic and professional settings. Educators are tasked with equipping students with the skills necessary to analyze and interpret information effectively. However, students and businesses can also learn these essential skills through available resources. SAS education resources
Modern software for statistical graphics automatically handles many details and graph defaults, such as the range of the axes and the placement of tick marks. In the days of yore, these details required tedious manual calculations. Think about what is required to place ticks on a scatter plot. On the
We often hear about cyberattacks, hackers, ransomware, and other nefarious deeds in the news, but not all data breaches are caused by third parties.
夏といえばひまわり。鮮やかな黄色は一輪でも強い存在感を放ち、我が家の食卓を飾る花でもある。ひまわりの花は常に太陽に向かって咲き、時間とともに太陽を追いかけるとされている。しかし、実際にはこのように動くのは芽生えから開花前のつぼみの時期までの話だ。 自然界にあるひまわりの成長には、太陽、気温、降水量、土壌など多くの要因が影響するが、これらの要因がどう関係するのだろうか。人工的な実験でも可能だが、たとえばひまわりの成長データを収集し、統計分析を用いることで最適な成長条件や栽培環境が特定できるはずだ。また、ビッグデータならではの機械学習アルゴリズムを使えば成長のルールやパターンを見つけることもできる。アナリティクスを駆使すれば（SASで開講中のアナリティクスコースはこちら⇒トレーニングコース | SAS）、収穫量の予測や最適な施肥方法、栽培条件も見つけられるだろう。実際、ひまわりの市場は世界で5.6兆円に登る巨大なマーケットなのだ。 ところで、ひまわりといえば気象衛星を連想するのは私だけだろうか。初代号が1977年に打ち上げられ、今度が10号になるが、最初は愛称で呼ばれていたものが後に正式名称となった。気象庁のサイト(気象庁 Japan Meteorological Agency)では、ほぼリアルタイムでひまわりの衛星写真がさまざまな切り口から見られるが、天気や防災に関する情報のほか、上記のような分析に欠かせない環境や気象のデータも豊富に提供されている。 2024年９月初旬 相吉
In SAS, DATA step programmers use the IN operator to determine whether a value is contained in a set of target values. Did you know that there is a similar functionality in the SAS IML language? The ELEMENT function in the SAS IML language is similar to the IN operator
A previous article shows how to implement recursive formulas in SAS. The article points out that you can often avoid recursion by using an iterative algorithm, which is more efficient. An example is the Fibonacci sequence, which is usually defined recursively as F(n) = F(n-1) + F(n-2) for n
Many well-known distributions become more and more "normal looking" for large values of a parameter. Famously, the binomial distribution, Binom(p, N), can be approximated by a normal distribution when N (the sample size) is large. Similarly, the Poisson(λ) distribution is well approximated by the normal distribution when λ is large.
SAS와 같은 글로벌 기업이 비즈니스를 할 때에는 글로벌 관점과 현지 관점의 균형을 맞추는 것이 중요합니다. 제품은 글로벌 시장 전반에 걸쳐 제공되어야 하고, 글로벌 경쟁력을 갖춰야 합니다. 반면, 고객과의 관계 구축은 현지 상황에 맞아야 합니다. 이는 적절한 현지 파트너와 협력을 통해서 강화할 수 있습니다. SAS코리아와 오랜 세월을 함께 동행해온 든든한 파트너,
As part of this year's IEEE Visual Analytics Science and Technology (VAST) Challenge, a group of SAS data scientists puit SAS Viya and related machine learning tools to the ultimate test - to identify individuals in a complex fishing network. Excitedly, the team received the Honorable Mention Award for Breadth of Investigation!
There are two programming tools that I rarely use: the SAS macro language and recursion. The SAS macro language is a tool that enables you to generate SAS statements. I rarely use the SAS macro language because the SAS IML language supports all the functionality required to write complex programs,
The SAS IML Language has a quirk with regards to functions that take no arguments. As discussed in the documentation, "modules with arguments are given a local symbol table." This is the usual behavior that programmers expect. However, the documentation goes on to state that "a module that has no
幼い頃、家の庭にたくさんのバラがあり、手入れが大変だった思いがある。トゲに刺されて痛い思いをしたり、傷になったりしたことを覚えている。興味深いことに、統計学の歴史にはナイチンゲールの「バラ」というグラフが登場する。 「白衣の天使」として知られるイギリスの看護師フロレンス・ナイチンゲールは、優れた統計学者でもあった。彼女は19世紀のクリミア戦争で看護師として派遣され、膨大な戦死者・傷病者データを分析し、多くの兵士が戦傷ではなく劣悪な衛生状態のために命を落としていることを明らかにした。その後、政治や行政に向けに「ローズダイアグラム」という革新的なグラフで報告した。 ローズダイアグラムは、円グラフの一種で、死因を視覚的に示すチャートである。月ごとの死亡者数を戦傷を赤、衛生状態や栄養不足を青、その他の要因を黒で色分けし、それぞれの面積で表現したものである（Florence Nightingale's Rose Diagram）。このグラフにより、衛生改善の必要性が明確になり、医療環境の改善が進んで傷病兵の死亡率が大幅に減少したのは言うまでもない。 統計学は記述統計と推測統計に分かれ、記述統計はデータの特徴を分かりやすく表現することを目的とする。ナイチンゲールの事例は、記述統計とデータ可視化が如何に重要かを物語っている。SASには「SAS Visual Analytics」という優れた可視化ツールがあり、基礎から上級までの関連コースも提供されている（SASトレーニングコース）。 2024年8月初旬 相吉
In SAS, the easiest way to draw random sampling from data is to use PROC SURVEYSELECT or the SAMPLE function in SAS IML software. I have previously written about how to implement four common sampling schemes by using PROC SURVEYSELECT and the SAMPLE function. The DATA step in SAS is
What sets the SAS Model Card apart from previous model cards is the use of descriptive visuals, to make model cards accessible to all personas involved in the analytics process, including data scientists, data engineers, MLOPs engineers, managers, executives, risk managers, business analytics, end-users, and any other stakeholder with access to the SAS Viya environment.
This article shows how to simulate data from a Poisson regression model, including how to account for an offset variable. If you are not familiar with how to run a Poisson regression in SAS, see the article "Poisson regression in SAS." A Poisson regression model is a specific type of
When using LLMs, managing toxicity, bias, and bad actors is critical for trustworthy outcomes. Let’s explore what organizations should be thinking about when addressing these important areas.
This article demonstrates how to use PROC GENMOD to perform a Poisson regression in SAS. There are different examples in the SAS documentation and in conference papers, but I chose this example because it uses two categorical explanatory variables. Therefore, the Poisson regression can be visualized by using a contingency
Learn how an intern integrated SAS Viya® and open-source code (Python) into a Machine Learning project to combine their strengths within the context of predictive modeling, and to show off the variety of ways this integration can be accomplished.
An article published in Nature has the intriguing title, "AI models collapse when trained on recursively generated data." (Shumailov, et al., 2024). The article is quite readable, but I also recommend a less technical overview of the result: "AI models fed AI-generated data quickly spew nonsense" (Gibney, 2024). The Gibney
Learn how to use SAS code (PROC HTTP) to read and write files from your Microsoft OneDrive, Microsoft Teams or SharePoint Online. You'll learn how to create a Microsoft Office 365 app, connect to it with SAS, and automate the integration with your office productivity environment.
A previous article shows that you can run a simple (one-variable) isotonic regression by using a quadratic programming (QP) formulation. While I was reading a book about computational geometry, I learned that there is a connection between isotonic regression and the convex hull of a certain set of points. Whaaaaat?
Since the pandemic began in 2020, the SAS IML developers have added about 50 new functions and enhancements to the SAS IML language in SAS Viya. Among these functions are new modern methods for optimization that have a simplified syntax as compared to the older 'NLP' functions that are available
Where GPT-4o is concerned for computer vision, SAS' Jonny McElhinney, Julia Florou-Moreno, and Priti Upadhyay advocate a trust-but-verify approach.
What's the difference between LENGTH and FORMAT in a SAS data set? This article shares the answer, with examples.
기업내에 AI/ML를 적용하기 위해, 업무 관점에서 시민 데이터 사이언티스트(Citizen Data Scientist, 이하 CDS)와 그 필요 역량인 데이터 문해력(Data Literacy)의 중요성이 높아지고 있습니다.(참고 : 데이터 문해력과 시민 데이터 사이언티스트의 필요 역량) 이와 연결하여, 데이터를 기반으로 신속하게 개발한 예측 모델을 업무 시스템에 통합 또는 활용하기 위해 IT 관점에서 해결해야할 과제와 접근 방안에 대해
Just like the SAS DATA step, the SAS IML language supports both functions and subroutines. A function returns a value, so the calling syntax is familiar: y = func(x1, x2); /* the function returns one value, y */ In this syntax, the input arguments are x1 and x2. The
