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Programming Tips
Aubrey Barfield 0
All hail the SAS programmer!

SAS offering free learning resources in celebration of programmers For more than 40 years, SAS programmers have crafted software and solutions that transform the world. From statistics to data science, to analytics and artificial intelligence, people writing code have architected a new economy with incredible opportunities. SAS Programmer Week honors

Analytics | Fraud & Security Intelligence | Risk Management
Ilkay Aydogdu 0
Three digital transformation challenge areas ahead for insurance providers in Turkey

Since the start of the COVID-19 pandemic, SAS has formed dedicated global teams to predict and monitor the pandemic’s course and identify the likely impact for customers. In Turkey, we have identified three main risk areas for insurers and have set out some strategies to help our clients respond, recover

Customer Intelligence | Fraud & Security Intelligence | Risk Management
Alexander Tikhonov 0
How banking in Russia is embracing digital transformation and resilience

It is becoming common to attribute huge changes in any sector to part of the global response to the pandemic. I’d argue that the pandemic has simply accelerated changes that were already happening in this sector. To test this hypothesis, I caught up with Alex Kwiatkowski, Principal Industry Consultant for

Advanced Analytics | Analytics | Data for Good
Melanie Carey 0
Take customer care to the next level with automated prediction in SAS Visual Analytics

What is automated prediction? Automated prediction, in less than a minute, runs several analytic models (such as decision trees, gradient boosting, and logistic and linear regression) on a specific variable of your choice. Most of the remaining variables in your dataset are automatically analyzed as factors that might influence your specified variable. They are called underlying factors. SAS then chooses the one model (champion model) that most accurately predicts your target variable. The model prediction and the underlying factors are then displayed. You can adjust the values of the underlying factors to determine how the model prediction changes with each adjustment.

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