Author

Alison Bolen
RSS
Editor of Blogs and Social Content

Alison Bolen is an editor at SAS, where she writes and edits content about analytics and emerging topics. Since starting at SAS in 1999, Alison has edited print publications, Web sites, e-newsletters, customer success stories and blogs. She has a bachelor’s degree in magazine journalism from Ohio University and a master’s degree in technical writing from North Carolina State University.

Analytics | SAS Events
Alison Bolen 0
Georgia-Pacific VP on building resilience in the era of disruption

If the last few years have taught us anything it’s this: business disruptions are not rare events. They are the norm. Today’s business leaders are grappling with logistics nightmares, economic upheaval, evolving consumer preferences, rapid technological advancements, regulatory changes, and armed conflicts. While it’s not possible to plan for every

Analytics | Data for Good
Alison Bolen 0
5 inspiring reads for Earth Day

From saving cheetahs to preserving fresh water systems, analytics plays a role in many inspiring conservation projects around the world. Read on to learn about a few of our favorites. 1. Protecting animals from extinction  Learn how analyzing footprints could help save cheetahs in Namibia and other endangered animals around

Analytics
Alison Bolen 0
Today we celebrate The Do Loop!

By almost any measure, Rick Wicklin is the most prolific and most popular blogger at SAS. Author of The Do Loop, Rick has been writing and publishing blogs at SAS since 2010, and today he publishes his 1,000th post on The Do Loop! To celebrate, I want to highlight some

Analytics | Data Management
Alison Bolen 0
임상 시험 데이터 공유, 암 치료의 새로운 가능성을 발견하다

암 치료는 매우 힘든 과정입니다. 따라서 환자별 최적의 치료법을 선택하고, 환자가 효과 없는 치료법으로 인해 필요 이상의 고통을 받지 않도록 하는 것이 중요한데요. 검사를 통해 치료의 진척 상황을 측정할 수는 있지만, 많은 환자들이 치료 과정을 변경하기에는 너무 늦은 시기까지 처방의 효과를 알지 못합니다. 그렇다면 만약 특정 암 치료의 효과를 수일

Artificial Intelligence | Machine Learning
Alison Bolen 0
12 machine learning articles to catch you up on the latest trend

Machine learning is a type of artificial intelligence that uses algorithms to iteratively learn from data and finds hidden insights in data without being explicitly programmed where to look or how to find the answer. Here at SAS, we hear questions every day about machine learning: what it is, how it compares to

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