In this multi-part series we’re going to explore a real-life example of operationalizing your analytics and then quickly dive into the technical details to make it happen. The phrase Operationalize your Analytics itself encompasses a framework for realizing timely and relevant business value from models, business rules, and algorithms. It […]
Building custom apps on top of SAS Viya, Part One: Where’s the value? was published on SAS Users.
Decision trees are a fundamental machine learning technique that every data scientist should know. Luckily, the construction and implementation of decision trees in SAS is straightforward and easy to produce. There are simply three sections to review for the development of decision trees: Data Tree development Model evaluation Data The […]
Build a decision tree in SAS was published on SAS Users.
Analytics is playing an increasingly strategic role in the ongoing digital transformation of organizations today. However, to succeed and scale your digital transformation efforts, it is critical to enable analytics skills at all tiers of your organization. In a recent blog post covering 4 principles of analytics you cannot ignore, […]
Analytics for everyone with SAS Viya was published on SAS Users.
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 […]
Discover Visual Analytics Report Paths with REST APIs was published on SAS Users.
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.
How SAS Visual Analytics’ automated prediction takes customer care to the next level was published on SAS Users.
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.
Expanding lengths of all character variables in SAS data sets was published on SAS Users.
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 […]
Learning to think like SAS was published on SAS Users.
Cast your ballots for the SAS Support Communities, nominated for two categories of the Khoros Kudos Awards: Best-in-Class: Community and Bottom Line Savings Rock Star.
Cast your vote! SAS Support Communities are on the 2020 Khoros Kudos Awards Ballot! was published on SAS Users.