Editor's note: This blog post is part of a series of posts, originally published here by our partner News Literacy Project, exploring the role of data in understanding our world. Infographics are one of the most visual ways to tell stories with data. They are designed to catch the reader’s eye, and they use
Last year, I wrote more than 100 posts for The DO Loop blog. In previous years, the most popular articles were about SAS programming tips, statistical analysis, and data visualization. But not in 2020. In 2020, when the world was ravaged by the coronavirus pandemic, the most-read articles were related
코로나19가 광범위하게 확산되면서 생산활동 중단, 소비 감소, 교역 감소 등 세계 경제에 심각한 타격이 이어지고 있습니다. 이 충격파를 최대한 완화하기 위해 각국 정부는 다양한 재정적 지원을 투입하고 있습니다. 그럼에도 대부분의 기업과 개인은 코로나19로 경제적 어려움을 겪고 있으며, 이로 인해 은행에서는 다음과 같은 과제에 직면하고 있습니다. 여신관리 코로나19의 영향을 가장 크고
지난 글에서는 기존 데이터 분석의 한계와 현업 사용자가 데이터 분석을 해야 하는 이유, 그리고 시티즌 데이터 사이언티스트가 되기 위한 조건을 알아봤습니다. 그렇다면 프로그래밍 기술이나 전문적인 분석 기술에는 능숙하지 않은 현업 사용자가 어떻게 데이터를 분석할 수 있을까요? 전문가 영역이었던 데이터 분석이 일반 현업 사용자로 확대되는 여러 움직임은 오래전부터 있었습니다. 그 가운데
지금처럼 빠르게 변화하는 비즈니스 환경에서 지속적인 성장을 이루기 위해서는 경영진과 분석가, 현업 사용자 등 기업 구성원 모두가 필요한 인사이트를 제때 확보하고, 이를 기반으로 최상의 결정을 내리고, 필요한 조치를 취할 수 있어야 합니다. 누구나 쉽게 데이터를 들여다보고, 탐색하고, 이해하고, 분석할 수 있는 단일화되고 통합된 분석 환경이 필요한 이유입니다. 본 기고문에서는 시티즌
Have you been stuck at home, dreaming up the next big trip you'll take after this pandemic is over? How will you pick a really cool location to visit? Perhaps you can ask your friends for suggestions. My co-worker (and lunch buddy) John recommended the Grand Prismatic Spring. Here's a
May you be healthy, safe, and surrounded by those your love this holiday season! We're looking forward to seeing you in the new year. Until, check out the RFC's Video Library for Kasey's 12 Days of Fit-mas Workout, recordings of our live streamed classes, guided meditations, and crafts and more! Or,
Romania’s energy and utilities market is thriving. The country has a high level of energy independence, thanks to oil and gas reserves in the Black Sea, and there is also activity in the solar energy market. However, many utilities companies are struggling to make appealing offers to customers, and there
In der EU und weltweit nehmen die Fälle von Identitätsdiebstahl von Jahr zu Jahr zu. 2019 stieg die Quote um 18 Prozent auf 223.163 in Großbritannien im Vergleich zum Vorjahr an. Damit fielen 61 Prozent der in der National Fraud Database erfassten Fälle auf den Tatbestand des Identitätsbetruges. Innerhalb von
A good public transportation system is crucial to develop smart cities, particularly in great metropolitan areas. Network optimization algorithms can be applied to better understand urban mobility, particularly based on a multimodal public transportation network.
When you perform a linear regression, you can examine the R-square value, which is a goodness-of-fit statistic that indicates how well the response variable can be represented as a linear combination of the explanatory variables. But did you know that you can also go the other direction? Given a set
Tis the season for my annual, fun Christmas themed blog post! This is the seventh year and my tenth song. I hope you enjoy this 2020 holiday song (to the tune of Rockin' around the Christmas Tree). Hackin around the Decision Tree at the SAS party hackathon Data science algorithms
The Smart Cities movement continues to forge ahead and evolve, led by innovative municipalities of all sizes. One of the towns at the forefront is Cary, North Carolina, adjacent to the Research Triangle Park and home of the SAS world headquarters. Cary Chief Information Officer Nicole Raimundo and her team
Predictive models are a critical component for automated and augmented decision making. As this deployment pattern becomes more widely adopted, two competing priorities emerge. How can we deliver more models faster while being certain of accurate and consistent performance? The key to solving this dilemma is in the automated testing
A note from Udo Sglavo: This post offers an introduction to complex optimization problems and the sophisticated algorithms SAS provides to solve them. In previous posts of this series, we learned that data availability, combined with more and cheaper computing power, creates an essential opportunity for decision-makers. After looking at network analytics
It takes a lot of companies collaborating in a lot of new and different ways behind the scenes to make AI work seamlessly on the front lines. We see this all the time in our work on AI. Processing power is one of the most obvious examples – when clients
Do you know that you can create a vector that has a specific correlation with another vector? That is, given a vector, x, and a correlation coefficient, ρ, you can find a vector, y, such that corr(x, y) = ρ. The vectors x and y can have an arbitrary number
If you have plotted data on a map, you have probably tried to estimate the geographical (or visual) 'center' of map areas, to place labels there. But have you ever given any thought to the "center of population"? This is one of the myriad of statistics the US Census Bureau
In this article, we summarize our SAS research paper on the application of reinforcement learning to monitor traffic control signals which was recently accepted to the 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada. This annual conference is hosted by the Neural Information Processing Systems Foundation, a non-profit corporation that promotes the exchange of ideas in neural information processing systems across multiple disciplines.
NOTE: this is a repost of a blog I wrote a few years ago. As I have been receiving frequent questions and requests for help on this topic recently, I thought it made sense to republish. Where to start: Knowing when a parent needs help, and what kind Many times
Editor's note: This blog post is part of a series of posts, originally published here by our partner News Literacy Project, exploring the role of data in understanding our world. Every day people use data to better understand the world. This helps them make decisions and measure impacts. But how do we take raw
Let’s flash back to a simpler year. I don’t want to date myself, so think circa 1990s. I remember sitting with my now husband watching Ken Burns’ documentary Baseball when I was first introduced to Doris Kearns Goodwin. She didn’t just know baseball – it was part of her DNA. She was smart, funny and a storyteller. I became a fan that day, and only came
The changes we have seen during 2020 have prompted a lot of soul-searching. Around the globe and across industry sectors, companies are looking at ways they can improve how they do business. My conversations with clients suggest manufacturing companies recognize we have reached a tipping point. Adopting analytics and using
A segmented regression model is a piecewise regression model that has two or more sub-models, each defined on a separate domain for the explanatory variables. For simplicity, assume the model has one continuous explanatory variable, X. The simplest segmented regression model assumes that the response is modeled by one parametric
지난 텍스트 분석 시리즈 2편에서는 보험사의 데이터를 이용하여 예측 모델을 개발하고, 모델의 성능을 개선하여 고객 행동에 대한 예측도를 높이는 방법을 살펴봤습니다. 이번에는 영화 리뷰 데이터를 사용하여 분류 규칙을 개발하는 과정을 SAS Visual Text Analytics를 중심으로 알아보겠습니다. SAS Visual Text Analytics(이하, VTA)는 대용량의 비정형 데이터로부터 쉽게 인사이트를 추출할 수 있도록 설계된
We seem to be in the height of webinar season, so please add one more to your calendar, brought to you by SAS, CT Global Solutions, and the International Institute of Forecasters: I'll be delivering a short introduction, covering the disappointing state of real life business forecasting in contrast to
Banks don’t like to publicise it, but there’s already a place on most high streets that offers everyday banking services: the Post Office.
This resource is designed primarily for beginner to intermediate data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest. A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is “which algorithm should
지난 텍스트 분석 시리즈 1편에서는 텍스트 토픽을 분류하여 빠르게 인사이트를 확보하는 방법을 소개해드렸습니다. 이번에는 텍스트 데이터를 기반으로 고객의 행동을 예측하고, 예측 모델링의 성능을 개선하는 방법을 알아보겠습니다. 이 작업에는 SAS의 머신러닝 솔루션인 SAS Visual Data Mining & Machine Learning(VDMML)이 유용합니다. 지금 이 시간에도 수많은 데이터 분석가들은 모델이 높은 성능을 발휘하도록 다양한
One purpose of principal component analysis (PCA) is to reduce the number of important variables in a data analysis. Thus, PCA is known as a dimension-reduction algorithm. I have written about four simple rules for deciding how many principal components (PCs) to keep. There are other methods for deciding how
