SAS Viya is an open analytics platform accessible from interfaces or various coding languages. REST API is one of the widely used interfaces. Multiple resources exist on how to access SAS Visual Analytics reports using SAS Viya REST API. For example Programmatically listing data sources in SAS Visual Analytics by
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.
SAS' Leonid Batkhan reveals how to change lengths for all character variables in a data set and all data sets in a data library to facilitate data migration to Unicode encoding environment.
The most fundamental concept that students learning introductory SAS programming must master is how SAS handles data. This might seem like an obvious statement, but it is often overlooked by students in their rush to produce code that works. I often tell my class to step back for a moment
Let's learn how to prompt for a date range in a SAS Visual Analytics report using control objects such as sliders, drop-down lists, and text input.
You want to use an API to retrieve data and process it with SAS. How do you do it? PROC HTTP offers the features of the cURL command within your SAS code.
SAS instructor Raymond Thomas touts the benefits of Report Center, part of SAS Environment Manager Extended Monitoring.
SAS instructor Raymond Thomas describes a typical day in the life of a SAS Administrator.
Turn analytical models into business value and smarter decisions with this special collection of papers about SAS Model Management. Without a structured and standardized process to integrate and coordinate all the different pieces of the model life cycle, a business can experience increased costs and missed opportunities. SAS Model Management solutions enable organizations to register, test, deploy, monitor, and retrain analytical models, leveraging any available technology – including open-source models in Python, R, and TensorFlow –into a competitive advantage.
SAS' Leonid Batkhan shows you how to split a large data set into many by a subsetting by a number of observations to produce smaller, better manageable data sets.
