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Analytics
SAS Korea 0
SAS, ‘머신러닝운영(MLOps) 플랫폼’ 부문 리더로 선정

‘SAS 모델 매니저’, IDC 마켓스케이프 평가에서 머신러닝 운영 플랫폼 리더로 선정 기업의 머신러닝 모델 생산을 지원하는 광범위한 서비스 및 제품 제공 역량 보유 세계적인 분석 선두 기업 SAS가 이번에 처음 발간되기 시작한 ‘IDC 마켓스케이프: 전세계 머신러닝 운영 플랫폼 2022년도 벤더 평가[1] 보고서에서 리더 기업으로 선정되었습니다. IDC는 ‘SAS 바이야(SAS® Viya®)’에 포함된

Advanced Analytics | Analytics | Cloud | Machine Learning
Charlie Chase 0
6 advantages of using software as a service for grocery supply chain planning

You're not alone if you’re still seeing local grocery stores with empty shelves.  Food shortages are still lingering in 2023. Increases in consumer demand, labor shortages and shipping capacity restraints continue to interrupt supply chains, particularly for grocery retailers. These problems have persisted throughout the pandemic, as seen with the shortages

Work & Life at SAS
Alyssa Grube 0
Our SAS Culture Code

Assessing a company from the outside can be tricky business – but it shouldn’t be. That’s why we’re kicking off a series to pull back the curtain on the #saslife. From our values to our vision and (almost) everything in between, we’re giving a transparent look at what it’s really like to

Analytics
Catherine (Cat) Truxillo 0
5 keys to building stronger analytics teams

With so much complexity and change in the marketplace, organizations worldwide are leveraging opportunities to make better predictions, identify solutions and take strategic, proactive steps forward – which means that they increasingly depend on big data. In their quest for organizational resilience, however, companies find that numbers aren’t necessarily the secret

Analytics
SAS Korea 0
‘2023 SAS 해커톤 대회’ 참가자 모집

‘2023 SAS 해커톤 대회’ 참가자 모집  2월 28일 참가자 모집 마감! 당신의 아이디어를 기다립니다 세계적인 분석 선두 기업 SAS가 매년 전세계적으로 진행하는 데이터 분석 아이디어 경진 대회 ‘2023 SAS 해커톤(SAS Hackathon)’의 참가 등록이 오는 2월 28일 마감됩니다. 누구에게나 열려있는 SAS 해커톤 대회에서 우리 사회를 이롭게 할 당신의 반짝이는 분석 아이디어를

Advanced Analytics
Kevin Scott 0
Improving the detection of level shifts using the median filter

Time series data is widely used in various fields, such as finance, economics, and engineering. One of the key challenges when working with time series data is detecting level shifts. A level shift occurs when the time series’ mean and/or variance changes abruptly. These shifts can significantly impact the analysis and forecasting of the time series and must be detected and handled properly.

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